My mom is lying sedated and restrained. I don’t know where things go from here.
I’ve been here before. The previous recoveries were miracles and I don’t think you can ask for more than one or two of those.
How much damage has been done in this breakdown? A frail 79-year-old fighting like a tiger for three days until she passed out, only to wake and fight again. Hurting her hand and instantly developing a haematoma and crying from the pain while still fighting.
She has a heart condition and is a stroke risk. Surely she couldn’t have got through this unscathed?
Authoritative voices
Five years ago I was told to institutionalise my mom in a public facility and get on with my life. That is a direct quote. From a professor of geriatric psychiatry. An acknowledged expert. His view: vascular dementia with no hope of recovery — only stepped decline.
I said no. I suppose we were lucky. I understand psychiatrists have legal authority to carry out institutionalisation themselves. The referring psychiatrist was shocked at the diagnosis and apologised. I took my mom home in worse condition than she had been admitted two weeks prior.
I found someone via recommendation who would listen. A geriatric psychiatrist prepared to consider the differential — PTSD and pseudodementia.
The first miracle
My mom had been beaten black and blue during a home invasion. After returning from hospital, she had a panic attack, a heart rate of over 200, and became catatonic. Then hysterical. She was admitted into hospital and we got her back after witnessing a miracle of psychiatric medicine.
We had a good period as I helped my parents move house and hopefully move on. When they were in the new house and I returned home, the next breakdown happened.
I live in Johannesburg. My parents live in Cape Town. There is no one else to help. I flew back and began again, working with a psychiatrist and trying to recreate the miracle. But drugs don’t always work and different drugs may not work at all. We moved through cocktails and titrations — one antidepressant after the other. There were no miracles.
Instead we had hell. My mom developed akathisia — a horrific condition where she could not stop moving and paced for 48 hours straight before I admitted her to a private institution.
There my mom got her diagnosis from the professor. He never actually met my mom. He reviewed his assistant’s files. I asked him how much doubt the limits of science would allow. He said he was 100% sure.
The roar
Before the first breakdown and readmission to hospital, I held my mom as she sobbed.
Maybe most children think their parents are special, as parents do of their kids. But many people say that about my mom. She is the most quiet, gentle and caring person imaginable. As I grew up she cared for every old person in our family, visiting and helping where others forgot.
She was broken by the violence. She saw the intruders smash my father to pieces. Fractured skull, brain contusion, damaged retina — he has never recovered his taste and smell, nor his full eyesight. She continually mentioned how the attackers were inhuman. She screamed as loud as she could to call for help. Her cries got neighbours’ attention and limited the attackers to nine minutes of hell.
But as my mom cried, she also talked about how everyone had looked after my dad. And that they had to. He was unconscious and desperately needed attention. But my mom was badly hurt too. Her head was bleeding, her face and body battered. After the beating, an attacker had jumped on her face and chest after she had fallen to the floor. And when they left she called all the attention to help my dad, as she needed to.
But no one heard her silent whispered cry.
The whisper
I will never forget my mom’s voice over a neighbour’s cellphone as she cried about what had happened to my dad minutes after the attack. I sat in my study in Johannesburg on a Sunday night, helpless, and struggled to get words out. Then I called family and friends to get to my parents as quickly as they could.
At the hospital my mom and dad were each put in isolation. It was COVID protocol. My mom lay alone and worried about my dad.
I went to the airport as early as I could the next morning after a sleepless night. I was worried I would not be allowed to fly with COVID restrictions. I messaged my team. I got on a flight.
I stood outside the hospital and waited until I was finally escorted to see my mom. She lay battered and bruised alone while crying about my dad. I was allowed to hug and comfort her as we both wore masks. I was not able to see my dad in ICU.
Later, as I tried to comfort her again as she broke down, she talked about how no one ever listened. Even her old boss, who had put her desk near a door as she froze each winter. There was a lifetime of whispers until life called on her to scream for someone else. But still no one heard her.
Patterns and spirals
The spiral was dramatic. The first time you see that is horrific. The person you know and love becomes someone you don’t recognise. My mother’s psychosis screamed all the way from the ambulance into the hospital.
Getting my mom back after the first breakdown felt unreal. I accompanied her to therapy and we welcomed my dad back. She got me to organise balloons for the homecoming to a family’s apartment we were kindly lent. My dad began a slow recovery but was spared memory of the terror he had endured by amnesia. My mom carried that alone.
A carer was the assistant to the miracle. Chipo worked on my mom’s recovery and became my mom’s protector. One of the best moments of the last five years is captured in a video of my mom visiting her old garden after regaining strength. She sat laughing with Chipo as Amber, my parents’ dog, struggled to contain her joy at seeing my mom.
I worked on my parents’ house in the day, starting with my cousin as we cleaned their blood from the floors. For three months I cleaned, renovated and first tried to rent out their house. I packed a family’s memories of a beloved house my mom’s father had rescued and cherished. I worked in gaps as I met with my team and clients remotely.
I visited my parents each evening for dinner as their recovery grew. My mom told me happily that whatever happened, she would always cherish that. But she also desperately wanted me to have the family house.
She returned to the house for the final packing. She managed that well. She had kept her mom’s ashes to scatter with her brother when he visited. But there was no time left and she buried her mom’s ashes in the beautiful garden she had created and now said goodbye to. She was so courageous as she took me to have a quick ceremony with her as she said goodbye. But she cried again as she said goodbye to her mom and her parents’ legacy.
We chose a retirement village. I believed in the place my parents eventually chose but had left the selection to them. There are seeds to a disaster and this may have been one. While I hung back, I worry my mother chose my choice. I missed a whisper.
I got most of the moving process done and returned to Joburg to kick off the new year. The old house was not yet rented and I would return to get that done.
When my mom sat down after unpacking, the next breakdown hit.
Echoes
I got straight back on a plane and returned to my parents.
This time was different. There was depression with the anxiety. I think that it all hit my mom as she sat and was finally confronted by the rest of their life. It was a new house with a way forward. But it emphasised what was lost and the uncertainty of what lay ahead.
I accompanied my mom to therapy and started the search for the right meds. There was ongoing delusional anxiety. All the time with a core reality. My mom had been the manager of finances and making ends meet. She couldn’t see how this was going to work going forward. She saw dependence and impact on me. From there the anxiety spiralled and my mom challenged reality.
The therapist gave up. Or perhaps I gave up on him. The psychiatrist was amazing and tried to help me after hours as I battled to hold on to my mom and find a breakthrough medical regime.
My focus had shifted from renting to selling the house under financial pressure. I left each morning at 04h00, mixed work and renovation all day and got home to look after my parents that evening. Sometimes looking after my mom happened through the night. Finally the sale happened.
My mom fought the depression so hard. She asked me to accompany her to introduce herself to her neighbour. My parents’ isolation had continued after moving in as further COVID scares limited movement and they had no immediate neighbours. I was so proud of my shy mom as she gave a gift to her neighbour and came home. It was a desperate attempt to move on when nothing really was.
There were also flashback nightmares. I held my mom as she relived that night of unspeakable horror. The meds could never erase that.
Then the akathisia hit and no one could cope, including me.
As I sat with my heavily drugged mom at the care facility admission, I asked what she would like to do when she got back home and was well again. She smiled weakly at me and said, “Make some new friends.”
Hearing a whisper
“I’m not sure why there have been attempts at cognitive assessment with so much anxiety in play.”
My mom’s clinical psychologist from after the attack had recommended her new geriatric psychiatrist as someone who had helped disprove incorrect dementia assessments.
I can cope with reality. But I like it to be evident. The psychiatrist said that there was no definitive basis for a dementia assessment, nor was there the ability to exclude the possibility. That could be where we ended up. But the right thing to do was to get on top of the anxiety and depression first.
The clinical psychologist had said to me, “Doctors are experts on medicine, but you are an expert on your mom. They have a 15-minute appointment — you have a lifetime with her.”
The new psychiatrist worked through me, trusting my observations. And we began to get my mom back.
One foot in front of the other
I had begun to learn that you cannot get too many steps ahead in managing crises and it is almost impossible to manage more than one at a time. Some longer-term view is essential, but mostly you need to focus on the next step. It’s no way to live perpetually, but it is the only way when each day threatens the next.
My mom had a scare with a seizure. Luckily I was there. I carried her to the car and rushed her to the ER. And luckily we met a Paarl physician who listened and who looked after my mom. We didn’t know what had happened, but my mom survived another scare and hospital stay.
As we saw my mom progress, other medical challenges emerged. My mom struggled with bladder pain and urgency. It seemed to be an outcome from all the medication. It was debilitating and a source of anxiety and depression in itself.
Surgery was unsuccessful.
And then we hit another breakthrough. An undiagnosed complicated UTI.
Women tell me that there are few things as debilitating as a UTI. Research shows that undiagnosed UTIs are a substantial contributor to misdiagnosed dementia.
My mother made another leap forward after IV antibiotics.
There are periods of a history like this one that compress in retrospect. In reality it was months of hell. There were multiple doctors who missed the diagnosis and who also looked at my mom and concluded dementia. Those who helped concluded more surgery. I tried multiple meds, including from compounding pharmacists.
But there were slow psychiatric and medical wins. My mom’s saviour psychiatrist, a family friend doctor and, finally, the right urologist considered my research and we agreed ways forward. We finally hit on the right combination of antidepressant, antipsychotic and a limited amount of benzodiazepine support. The IV antibiotics and an off-label benefit of another antidepressant resolved the bladder sensitivity. A doctor jokingly remarked I deserved an honorary doctorate in pharmacology.
The professor had said there are no improvements with dementia. Only plateaus before further declines. He flat out refused a differential diagnosis. My mom showed us one.
During this time, I lost a business team that had taken 15 years to build. I needed help.
Help
Miracles seem to need angels. Chipo had been the first. The clinical psychologist the second. My mom’s old physician, who continued to see her despite a new specialisation, was the third. That physician did the MRIs that she concluded showed age-related brain state rather than any vascular damage. The new psychiatrist the fourth. The Paarl physician the fifth. Annalisa was the sixth.
In crises, affordability and time are the challenge. And probably what most people struggle with. Most people probably fail mostly because they just cannot manage affordability or time. I couldn’t, and so everything came at the cost of other things.
Getting my mom a carer was crucial to being able to get back to my business and life. Finding someone to take over being my mom’s advocate was crucial. Annalisa was that.
They say that we all need an advocate in complicated medical issues when we are unable to fight for ourselves. I had been that for my mom. I knew in reversed roles she would have been that for me. Very few of us are blessed to have that kind of person in our lives.
Over time, the retirement village would describe Annalisa as my mom’s biggest fan. There were other carers too. But Annalisa would fight for my mom. And my mom would fight for her.
Over the next three years my mom gradually settled into a new life. There were nightmares. There were days of debilitating anxiety. There was gradual tuning of medication. She has had a remaining tremor from the medication which makes it difficult for her to eat by herself. She is dependent on help and self-conscious. People have spoken to me as if she has dementia in front of her, as though she wasn’t there.
Meanwhile, she retreated and is probably the village’s biggest library customer and most regular walker, accompanied by Annalisa.
More angels
People have so much to cope with in their own lives. They have to prioritise. And they move on.
A client CEO and friend said to me in the early days of my parents’ incident, “This is hard. But be prepared, it is going to get harder. Right now others are there with you, but they are going to have to move on. And you have a long battle ahead.”
He spoke from his personal experience. A drunk pedestrian had fallen in front of his car. He told how even his wife could not continue to share the intensity of what he was going through for as long as he did.
People did move on. There were many amazing people who rallied to my parents in the early days. Who contributed to a rehabilitation fund. Who signed the petitions against bail for the one perpetrator they caught. Who visited.
But after a time visits grew less, especially due to the distance to my parents’ new house.
My assistant, my team member who stayed and helped me rebuild my business, and friends were the angels for me.
Setbacks
No recovery is all plain sailing. My mom had progressed so well and, when out on a visit to the shops with visiting family, fell on an escalator and suffered a huge cut to her leg. The blood thinner caused massive bleeding and the trauma began again. Surgeries, hospitalisation and a long recovery started. Drug-resistant bacteria and a haematoma complicated things. It was a miracle that my mom did not lose her leg. It was also a miracle that the ever-present PTSD and anxiety did not reclaim her. The Paarl physician was my trusted anchor.
Again I was flying in and out. I was awestruck at my mom’s fight. She had fought for so long. And here she was fighting again. She and Annalisa started slow walks again, beginning with just short walks to the end of the road. It was a huge setback from her 3km walks to the nearby dam and back. After the second breakdown I promised my mom she would get back there. She had done so and now she was starting again.
My Dad
My dad does not hear whispers. He was spared the trauma of their attack through amnesia. Instead, his trauma was mostly related to my mom’s.
He battled to understand her difficulties and pain. He has had to be there when I and the carers are not, especially through the night. It is a lonely and frustrating place.
He does not understand PTSD. He rages against it. And it meant a lonely and frightening place for my mom.
Now
I’ve just flown to Joburg and back for a meeting and got back to my mom after 24 hours away. When I left my mom was screaming as she fought the insertion of a feeding tube. She cried at me that they were torturing her.
It was hell seeing her like that. The attending staff thought they were dealing with a dementia patient who had screamed and fought for three days. Now if she didn’t get medication and food, her body would start to shut down. Her kidneys were already showing signs of strain.
That morning I had asked for her doctor to be replaced. On the Monday after admission I agreed my mom’s medications with the weekend doctor. As I held my mom down on the Monday morning I managed to get in increased amounts of two of the key drugs. She ate lunch by herself that day sitting in bed. The staff couldn’t recognise her from the person from the night before. I went to my parents’ home to give my dad a chance that afternoon. When he returned he told me my mom was speaking gibberish again. By the time I got there, she was hysterical and I had to hold her down. She would now not take any pills. I typed meds into my phone screen with one hand while holding my mom down and asked a nurse to phone the doctor to authorise an injection. I held her until it was given and she passed out.
When I walked in on Tuesday morning I could hear my mom screaming. She was alone in her bed. There was no one looking after her. Her newly assigned doctor walked in and began arguing with me immediately. He would not hear that I had agreed with the weekend doctor to go back to my mom’s previous meds with an antipsychotic. He removed those and would not talk to me again until he got hold of my mom’s psychiatrist. He came back having agreed a different antipsychotic on the back of his incorrect understanding of the previous day. I held my mom down until the injection took effect and knocked her out. She was threatening suicide and fighting like crazy. In a brief period where I was asked to leave for a nurse to hold her while another took blood, she lashed out, hit her hand on the bed and in minutes a massive haematoma rose up because of her blood thinners.
During the day, I sent emails to the psychiatrist and found that my mom’s doctor had told him my mom had become more agitated after the Monday morning meds. Further, he misunderstood what pills my mom had had.
I have found that advocacy involves lots of time in hospital wards stalking doctors doing their rounds. When I spoke to the doctor on his afternoon round he became angry again. He shouted at me that my mom should be in a psychiatric ward and he was not a psychiatrist.
The Wednesday morning was worse. My mom was now heavily sedated, refusing food and medication. The doctor took me through her test results. At least he did that.
A further shouting was the final straw. When doctors aren’t interested in facts I think patients’ lives are at risk. I asked a sister the process to replace him and she offered to talk to him. She came back having managed to get his agreement. Another angel.
My mom’s old physician moved in quickly. The treatment didn’t change but the attitude did. I continued to sit with my mom and try to get fluid and meds into her. I managed the morning meds drop by drop.
I was leaving for Joburg after lunch. One of my mom’s carers had arrived to stand in for me when I left. I have found that hospitals rescue those in severe need, but sometimes people like my mom just survive them. Having someone who knows her there to advocate for her makes an enormous difference. Telling staff that she was reading and walking and a normal person six days ago can make a vast difference to how she is treated.
People see what is in front of them. When they see someone who is old and not making sense, they see dementia. When they see a young soldier returning from war with the same symptoms they see PTSD.
I’ve always been prepared to consider and deal with dementia. I’ve organised the MRIs to check and agreed prophylactic medication. But I have refused to accept a default diagnosis with no differential. Imagine it was you or someone you love – written off and denied recovery. Imagine there was no one to tell people that the person they saw was not you. Or imagine there was but no one would listen.
My mom’s brain is ageing. I do not know how this affects her and will over time.
As I travelled to the airport I got a call from the hospital. I had left the carer in tears as she helped the staff with my screaming mom as they inserted the feeding tube. As they took my mom to X-ray the tube, the carer passed out from high blood pressure. My mom was going to have a night alone and scared.
Last night I battled to concentrate on my meeting prep as I contemplated my mom after another setback, perhaps this time with real damage from a stroke. She had fought so hard that even as I held her down she would pass out briefly from the strain before fighting again. I had another bad night’s sleep as I imagined dealing with my mother disabled going forward. I felt I had run out of rights to ask for any more miracles.
The meeting went well and I raced back to Cape Town. I had a call with the psychiatrist in the car, corrected the week’s treatment history and we agreed a way forward. He emailed the Paarl physician immediately.
Hope
When I walked into the hospital, the nursing staff were smiling. The sister told me to go and see my mom. When I stepped into my mom’s hospital room, she lay there weak and tired. But peaceful and cognitively aware. She smiled when she saw me.
The nurses told me they didn’t recognise my mom from the person who had been brought in. I showed them photos of my mom after she had been assaulted. They were horrified. They could now see what had been whispered. My mom needed help. She was desperately crying from the terrors of PTSD, not from the irrecoverable ravages of dementia.
The saviour physician then phoned. My mom had a UTI. The culture results had come back. Two different bacteria, one antibiotic resistant.
I don’t know how my mom will recover from this. I have learnt we have a system of reserves we draw on. When those tanks empty, we fall in on ourselves. My mom’s tanks are always close to empty. Psychosis is when the mind’s protective mechanisms overreact and it becomes difficult to reach through and pull the person back. I have seen the power and the limits of psychiatric drugs.
I hope my mom has some fight left. She turns 80 in two months’ time. I have seen a shy, gentle person dig deep over and over again as I have encouraged her. She has been walking over a kilometre in the morning each day in response to my encouragement. The first time she managed that after the leg injury, she smiled into the nightly video call with pride and said to me, “Ask me how my walk went.”
I hope she can rebuild some reserves once again.
—
** There were so many more angels along the way. From the neighbours to the friends to the colleagues and the clients. Some like my mom’s nurse neighbour have played a recurring role. Others just said a kind word at the right time.
9 minutes of unbelievable violence changed everything. You – the kindest, gentlest person imaginable – were robbed of peace forever.
Four years later and there is still evidence of how you were beaten. But deeper than this is what you experienced.
You have faced the horrors of PTSD and depression and faced an ongoing daily battle after a series of breakdowns. The medications that have helped you survive, drown you in fog and have debilitating side effects. Your physical crises and injuries which have forced multiple restarts.
You have faced increased isolation as people moved on – especially after that first year when even I had to return to Joburg to try and rebuild my business for myself and my team. And as you pulled back from technology or were unable to manage it with your physical limitations. As people wrote off your condition to dementia.
Medical professionals failed you with misdiagnoses.
Medicines that should have worked didn’t or stopped working.
In all of this, your kindness, gentleness and character shone through. Your unending love for me, your smiles when you see me. Your concern and support.
Nurses fight to be allocated to care for you – you are unfailingly polite and kind and never fail to preface any request with a “please” and then ensure you thank people.
You have really tough days. And then days like yesterday when you found inspiration in the book “Mao’s Last Dancer” which you devoured in no time and told me about with such admiration.
I wish I could have done more and been more effective. I see mistakes I made or things I didn’t do and know there are things I do not know about – what I should have done or not done.
I try to learn from you and everything I confront.
Through all of the last four years I learnt about the life challenges that almost every person faces – be those aging parents, illness, mental health, relationship difficulties, divorce, cancer – and how to empathise more.
I learnt about angels – as you were to so many family members and me, as the few doctors who cared were, as my team members and assistant were. Clients and team members who believed. Friends. And even just the kind and thoughtful comments from a few wise people.
I have learnt about loss – especially of those who are close – and lack of control and influence. Again and again.
As I see you every four months, there are fewer and fewer times with you in my future.
Nothing hurts more than losing people you are close to.
During the challenges I’ve faced over the past few years, some of the loss of those people happened due to toxic chat. I know, because I was told about it or given the clues.
When things are tough and people are having a tough time – especially in a business team – it is natural for people to talk with one another about the tough time they are facing and how another person may be contributing to that, being unfair, etc.
With that chatter, perspective and history is usually lost. But more critically, incorrect views can go unchallenged and misrepresentations can grow a life of their own.
As one of my team expressed unhappiness and referenced some data points last year, I followed up and checked their assertions. The “facts” they threw into an emotional argument were wrong. I never got to correct them before the team member moved on. From there, those “facts” might easily have been repeated (and seemingly were) and poisoned others views. All previous virtues get forgotten in moments like that and the poison spreads.
Griping, white-anting, etc destroys teams. But more than that, it destroys relationships. The poison revises the past and remains the memory.
Rebuilding a business is hard. But friends and team members who were lost are gone forever. Beyond that, it can result in losing people you love and care about. And it did.
I am Awe-Inspired and Terrified (to quote a friend)
I have said that I had an AI moment a few weeks ago (here). It was like I got hit by a lightning bolt.
It was such a simple thing – I saw Matt Wolfe embed a very targeted GPT request into a workflow. It’s a five month old video.
That was it. My world changed. I could see that using a GPT iteratively for inference-based micro tasks would change everything.
Since then I have watched what must be nearing a hundred of hours of video, read voraciously, experimented in deploying AI in Python and enabling local AI in large parts of our business platform. It has felt like I am living in science fiction.
The Current Dominant Consumer State of AI
I think many people have been using ChatGPT as kind of an advanced search (hallucinations and all). As they become more sophisticated they might start using it as an advisor and coder and use that for software configuration. The combination of those two can with be used for diagnosis and then correction.
This extended use can shortcut work or resolve unresolved errors. That is a big impact on productivity.
AI as a Workflow Step
With my new interest, my Google Assistant newsfeed showed me Sam Altman discussing how GPT-5 will include the ability to launch agents. I think this is where productivity really begins to explode, where multiple tasks in multiple apps on multiple servers can be chained together in a free-form fashion, as opposed to a deterministic workflow.
I think that will cement OpenAI not just as a chatbot and LLM but the front end to a ecosystem of models , orchestration and agents. The ChatGPT web or mobile interface already appears to be moving towards this.
While interacting with ChatGPT and watching various videos about AI, it is clear that ChatGPT is interface to more than the large language model . It is already calling agents for certain tasks. for example when we ask ChatGPT to draw a graph it spawns a python shell and generates a graph using that shell and that seems to represent a combination of the LLM which is good at inference and a python agent which is good at deterministic output. Perhaps the future will reflect a combination of these capabilities in a way that’s imperceptible to us where they combine and leverage and check one another.
Agent Visionaries
I am a bit late to this. Andrew Ng has been talking about agentic workflows for a while. At Sequoia’s recent AI open day (excellent – watch the whole day here), Andrew showed the impact of Agentic Workflow on the performance of underlying LLMs. It is staggering. It elevates lower capability LLMs to higher level performance – e.g. ChatGPT 3.5 outperforming ChatGPT 4.
Source: Andrew Ng – Sequoia Capital AI Ascent Day
I think what we’re going to see is the emergence of an AI agent economy and ecosystem.
In what seemed like simultaneous to my epiphany, Devin launched. It shook the software development industry. Suddenly macro level tasks that were outside the realm of GPT prompts due to their limited context window and lack of real-time content were accessible. Devin can independently execute an entire software development project. Within days, OpenDevin launched – an open source version. And then the open source Devika.
Devin is already working on tasks that are listed on Upwork. Devin solves it and then earns the bounty.
Devin represents a system using an overall orchestration platform for software development together with the ability to spawn agents and iteratively interact with LLMs.
I think that concept could be extended into other domains like research.
This will move exponentially faster now. I believe we will see agentic tools for provisioning IT servers and end-users in the next few weeks – it is an obvious candidate.
I think the above also will result in the atomization and extension of AI at multiple levels.
Agents as a Solution to Yann LeCun’s Hierarchical Planning Challenge
I wrote about Yann LeCun’s (Meta Chief AI scientist) criticism of the current AI models as a path to AGI here. He highlighted the inability of current LLMs to cross from the language domain and the complexity of hierarchical planning – his example: a trip from New York to London.
I think that the use of LLMs for discrete inferential tasks within broader workflows challenges that. Perhaps what we will see is a disaggregated model of AI performing these complex tasks and freedom from the context window limitations of current LLMs.
In my naive thinking, I imagine this to be like the specialist areas of the brain (e.g. the visual cortex) processing small discrete specialist tasks within a broader process.
Software Development Project Execution as a Model for Other Domains
Software development is similar to strategy consulting in that it requires a mix of hierarchical planning with lots of complexity and then execution. The idea that AI replaces a consultant is perhaps a long way off. The opportunity to execute a task exceptionally well remains a current opportunity. However, the combination of AI within consulting workflows and perhaps agents in ChatGPT5 is very exciting.
Researchers working with BCG (here) found that application of AI in task completion led to the following improvements:
Increased Productivity: Consultants using AI completed significantly more tasks compared to those without AI. Specifically, they completed 12,2% more tasks on average.
Enhanced Quality of Work: The quality of work, as measured by human graders, was significantly higher for consultants who used AI. The improvement in quality was more than 40% higher compared to the control group without AI.
Faster Task Completion: Consultants using AI were able to complete tasks 25,1% more quickly, indicating a substantial increase in efficiency.
Benefit Across Skill Levels: The study found that AI augmentation benefited consultants across the skills distribution. Consultants below the average performance threshold experienced a 43% increase in their scores, while those above the threshold saw a 17% increase compared to their own baseline scores without AI.
These are early days. However, let’s consider that summary again:
“For each one of a set of 18 realistic consulting tasks within the frontier of AI capabilities, consultants using AI were significantly more productive (they completed 12,2% more tasks on average, and completed tasks 25,1% more quickly), and produced significantly higher quality results (more than 40% higher quality compared to a control group).”
I think the challenge will be to structure consulting tasks into defined workflows so that discrete tasks suitable for AI and application of agents can be identified and automated. However, few would have thought software development was significantly less complex and could be challenged so quickly.
The Atomization of AI
We are already seeing “mixture of expert” LLM models – like the recent open source release of DBRX. This splits LLMs into expert domains and then chooses combinations to best answer a query. This has the benefit of smaller less costly LLMs and very fast tokens-per-second outputs. This is critical for agentic workflows that need to rapidly and iteratively execute calls to LLMs.
Perplexity.ai provides a free and paid for front end to multiple LLMs (e.g. OpenAI, Mistral, etc). This too allows some of the atomization too via aggregation at the front end. In the last few days, we now have an open source app that accomplishes this too.
Workflow, integration and agent tools like WSO2, Zapier, Make, Huginn and n8n clearly become infinitely more powerful using AI agents for embedded inferential tasks. Scanning unstructured text and returning a structured JSON string is trivial for an inferential agent.
There is quite a lot of talk that ultimately this will breed an AI OS – an OS of AI with agents and orchestration. And that will sit on top of AI optimised hardware (for native neural networking capability). This is already the direction Nvidia is going.
The Rise of Agent Ecosystems
I think that we’ll see agent ecosystems around particular software and tasks. For example, take the WordPress plugin library. Perhaps instead of marketplaces of plugins will see functionality requests being satisfied through AI.
In areas such as R and python, the library ecosystems will become dynamic where functionality will be extended by agents and AI. Libraries might represent a static view of functionality at a point in time before being further improved by agents – much as they represent a static version today before further human improvement.
The End of Application Marketplaces as a Monetization Mechanism?
Applications such as WordPress, SuiteCRM or others combine open-source software with marketplaces for extended functionality. This could be a method to monetize functionalities that are in high demand but not part of the free core system. It also presents an opportunity to bring in more developers.
On-demand agent-driven software development could destroy a current means of monetizing core open-source software.
In many cases, the existing plugin libraries attract huge subscription fees for extended functionality, particularly in business niches.
Data as a AI Building Block
Agent ecosystems could lead to interaction with broader application areas like finance and underpinning those application areas will be data – not just training data, but real-time data.
Perhaps instead of LLMs being trained on custom data sets we will move to an interaction between capable LLMs and dynamic data sets – like document libraries, knowledge bases, financial data, etc. LLMs and agents will then be used in real-time to interact with up-to-date data. In a very basic way, I think we already seeing something like that with ChatGPT’s ability to search the web and feed results into its responses. Retrieval Augmented Generation (RAG) is already part of PrivateGPT – a means of locally implementing LLMs to interact with private data.
Winners and Losers
The medium-term AI short trade is surely obvious now.
I can see the losers in the new world – those performing repetitive tasks with unstructured data. For example (at a very discrete level), isolating contact details from an email is a surprisingly difficult deterministic task via parsing rules. It becomes trivial with AI. There are hosts of admin intensive tasks in this kind of domain. Repetitive tasks such as Search Engine Optimisation change completely.
IT system administration, helpdesks, etc – they are a huge target. Software development as indicated above. System transformation and integration. AI can untangle logic in legacy systems and rebuild it better in modern platforms.
Call centers are already under threat. Klarna released outputs showing that customers received better (or no-worse) service from automated chatbots. Those chatbots handled two-thirds of customer service chats in their first month.
The creator economy is hugely impacted by AI. I have seen people claiming to generate multiple (10+) videos via AI within 1 hour and launch into Youtube and monetise via AI tuning to exponential (viral) growth. Given that AI strength right now is generative, I think there is a likely explosion of content. At some point this makes stored content overwhelming and meaningless (the “dead internet”). Ultimately any content can be generated real time. That blows the creator model and associated monetization. That feels like a very current coming change.
What happens to the Google goldmine – search with advertising? I think search is crucial to combined use with AI. LLMs are static and search provides context and currency. I think most people misinterpret AI as a replacement for search. That is poor use, But what people do, will be. A mitigating step is that AI summaries already present in Google and Bing. Perhaps the broader implication is the rise of subscriptions or on demand paid-for opt-outs from advertising impregnated results. Currently top-end AI is only meaningfully available through paid subscription (e.g. GPT4) or behind paid service (e.g. Microsoft Copilot). So hybridisation is probably the outcome.
Software firms could be major losers as functionality is generated and customised for end users. Microsoft is moving exceptionally quickly. An AI operating system with ecosystem integration must be a medium to long-term prospect.
There are lots of opportunities in manufacturing, supply chain and logistics. This was an early target for Andrew Ng – but he does talk of the difficulties in using AI in fields like quality control, etc. Not a slam dunk and probably lots of opportunities on small tasks, particularly related to integration with IoT.
The potential disruption in security, law enforcement, etc is enormous. AI is already being used for monitoring camera footage for alarm conditions – this happened a long time ago. China has built a surveillance state on the back of AI-driven surveillance. I believe most of these were based on custom and tailored development. Agentic workflow extends customised opportunities to a huge market.
Foundational layers win for the forseeable future – computing power and energy – so yes, obviously NVIDIA.
However, AI could obsolete IP – i.e. it might design better software, drugs or even a GPU. Hinton and others are talking of a cure for cancer. An optimal GPU for another NVIDIA seems trivial. For example – it takes a PhD student 5 years to map one protein. Deepmind did 200 million proteins in no comparative time. AI potentially improves exponentially as it is applied to the full engineering stack – from materials, to hardware to software.
Elon Musk has mentioned a few times that beyond chips, it becomes as simple availability of other components such as step-down transformers for computing processors in the near term (within the next year).
If you go more foundational than that, then silicon and other materials win no matter what.
But there must be something more clever than that. Probably the clever stuff is which fields take off due to being changed completely – health and pharmaceuticals is obviously one area.
One of the most hopeful outcomes (beyond improved healthcare) is improved education. It is a short step to a chatbot for every poverty-stricken child on a smartphone (probably with a LLM on their phone) – with the whole of the internet as training data. That kid gets a perfect (soon) teacher instead of an poorly trained one in a badly resourced classroom. That also talks to the extension of AI to a huge target base as opposed to Google search only being available to a more affluent segment of the population. Monetisation becomes big issue – but you could displace badly spent money to subscriptions – e.g. education budgets.
Larry Summers believes AI is coming for the cognitive class. Fields like asset management and wealth management will surely be transformed. AI supports algorithmic trading and investing, removing effects of bias and performing arbitrage to the extent it still exists. Perhaps it scales to far bigger effects than this.
I think we realistically can expect to be able to analyse all standard financial measures via AI – e.g. dump investment Due Diligence data into AI and get an analytical output. Then that can be scaled to all publicly available data. Anthropic’s Claude is already better at ChatGPT at this. Private data access becomes a game changer.
Managing AI hallucinations and testing will be absolutely critical. Perhaps just like how transformers in LLM model training turned out to be one of the biggest AI breakthroughs, so will checking in an atomized AI architecture be, with agents performing this task. This is already happening in the software development tools mentioned above.
There is surely an anti-AI reaction – a bit like people going back to LPs and film photography. This exists at many levels, and perhaps face-to-face and relationships become more sought after.
The old big spender is what it always was – defence. Hinton mentions US defence now and again. AI clearly has immediate application to misinformation bots or monitoring. China has an enormous AI-driven surveillance state.
There are lots of conspiracies on OpenAI cracking encryption (as being the reason behind Altman was temporarily fired). Apparently Ilya Sutskever is now only focused on AI ethics and security. I am not sure of inference being able to break encryption. Maybe I am just scared of the consequence. And AI engines are becoming better at maths. JP Morgan have had a team working on defence against AI encryption cracking for a few years. If AI was close, the genie would be out of the bottle. I imagine that Russia and China will be racing to leverage all the open domain and spied AI progress to get ahead. Cleary the world will pay anything to defend against this – if it is defendable.
Broader Implications
There must be room for game changing combinations of technology. Clearly energy and AI supercomputing is one area. Microsoft and Amazon have both pursued adjacency to nuclear power sources to cater for the massive energy needs of current AI. Sam Altman talks of the potential of nuclear fusion and perhaps fission. The combination of AI with quantum computing is an exciting or scary prospect. These combinations become nearer term when perhaps AI is deployed to solve the road-blocks to progress in those domains.
For me, the most scary part of the pace of development is that while the dominant actors such as OpenAI, Anthropic, Amazon, Microsoft and Google might be scrambling to manage the potential for a bad AI outcome, this genie is well and truly out of the bottle. While rigorous testing, LLM ablation and other techniques might mitigate bad outcomes, jailbreaks are still a problem. However, the bigger problem is surely that developers are feeding off one another at a rate of knots. Previous thoughts on roadblocks to AI development such as what were thought to be diminishing returns on LLM scaling have proven to be false and encouraged others to rapidly intensify their efforts. The scope for bad actors such as hacker groups to use localised open source LLMs as an inference engine in a hacking agentic workflow seems obvious and immediate. Or to increase effectiveness of spam and cyberscams. Or to launch massive paid misinformation campaigns. At a Nation State level, restrictions baked into massive LLMs are not relevant if researchers build their own.
But, more immediate to most of us, is that in the current term, application of AI to discrete tasks for inference is happening now and agentic workflows change the world today.
Headline summary: 1. Transcription to phone and then AI improvement helps me get work done on the move.
2. Speech-to-speech interaction with ChatGPT on my phone makes for an interactive learning process.
Transcription as a Life Hack
Transcription is essential for us due to the advancements in voice notes for meetings, video calls, etc. Although transcription services are expensive, the rapid pace of development and the productivity boost they offer make them a worthwhile investment.
In our ongoing research into self-hosted transcription services, I’ve evaluated using Whisper, subscription services like Otter.ai, and conducted further research into GPT models.
Should we choose the self-hosted option, we’d require a server equipped with GPU technology for audio-to-text conversion. I’ve considered refurbished AI servers, but options are limited in South Africa.
I’ve also looked into old mining rigs, but due to the AI and crypto boom, prices are inflated. A high-spec server from the US can cost anything between $500 to $7500 before huge shipping costs, with GPUs not included at the lower end, and Tesla NVIDIA GPU prices being particularly high. This could easily amount to anything from R200000 to a million rand for an AI server, making subscription services a more feasible option.
So, why not just start with what’s available?
I set Google’s voice-to-text as my default keyboard on Android to transcribe my thoughts into notes. The initial output was quite rough, with many incorrect word choices. Therefore, I activated Microsoft Copilot from my Android keyboard and asked it to clean up the transcription from my note, which it did impressively. This process can be frequently repeated.
One of the benefits is that I can convert ideas, thoughts, and instructions into written form much quicker and with less effort than before. This not only frees up my time but also allows me to increase my output, having a cumulative effect on productivity.
Previously, many of these notes and ideas might have remained in my head and never been shared, impacting delegation and leaving execution solely to me. Now, as I have numerous concurrent thoughts about clients and projects, I can quickly transcribe them into notes, refine them through GPT, transform them into tasks, and share them with team members. It’s quite remarkable.
I believe the process of using live voice-to-text transcription, then chaining it into CoPilot for improvement and then back into a notepad, feels stilted and not as productive as it could be, although it is obviously a significant gain in itself.
I think that recording voice notes on an ad hoc basis and then uploading and transcribing them for improvement is probably a better route.
However, long form transcriptions break ChatGPT’s context window and iterating backwards and forwards with sections makes for a difficult process.
Using an Iterative AI Approach to Improve Long Form Transcriptions or Essays
ChatGPT recommends the this iterative approach to transcriptions or even improvement of long-form essays (situational analysis or SA).
Break down the content: If you have a lengthy SA document, it’s useful to break it down into smaller sections or questions. This approach makes it easier for the model to provide relevant and focused responses.
Be specific with your queries: When asking questions related to the SA content, be as specific as possible. Specific questions lead to more precise answers, which can be more useful for your analysis.
Use clear and concise language: While complex concepts might be involved, try to phrase your questions in clear and concise language to avoid misunderstandings.
Sequential querying: If you’re exploring a complex topic, consider using a sequential querying approach. Start with more general questions and gradually drill down to more specific aspects based on the responses you receive.
Highlight key information: If you’re inputting a section of your SA for analysis, highlight or summarize key points you want the model to consider. This helps in focusing the response on the most relevant aspects.
Iterative refinement: Based on the initial responses, refine your questions or provide additional context to get more detailed insights. It’s often an iterative process to zero in on the most valuable information.
Summarization requests: For comprehensive sections of the SA, you can request summaries to capture the essence of the content. This can be a good starting point for deeper exploration.
Cross-referencing: If your SA involves multiple sources or documents, reference them in your queries to understand how they interrelate or to compare their perspectives.
Is it effective passing a section of a transcription to ChatGPT with the previously optimized sections for context? This iteration can be tedious – passing a section of a transcription to ChatGPT, along with previously optimized sections for context, can be effective, particularly for maintaining coherence and relevance in the conversation. Here’s why this approach can work well:
Context Preservation: ChatGPT can generate more accurate and relevant responses when it has context. By providing optimized sections of the transcription as context, you help the model understand the broader conversation or document theme, leading to more informed and appropriate responses.
Coherence: Including previous sections helps maintain coherence across the conversation. ChatGPT can refer back to earlier points, ensuring that the discussion flows logically and consistently.
Efficiency: Optimizing the context by selecting the most relevant sections can make the interaction more efficient. It prevents information overload and helps ChatGPT focus on the most pertinent information, improving response quality.
Customization: This approach allows for a degree of customization in how you interact with ChatGPT. You can tailor the context you provide based on what you’ve found to be most effective for your specific use case, whether it’s a detailed analysis, brainstorming session, or any other application.
However, it’s important to keep a few things in mind:
Context Limit: ChatGPT has a limit to the amount of context it can consider for each response (the token limit). Be mindful of this when selecting which sections to include as context.
Relevance: Ensure that the sections you’re passing as context are directly relevant to the current section you’re inquiring about. Irrelevant context can lead to less accurate responses.
Iteration: You might need to experiment with different approaches to optimizing context to find what works best for your specific needs.
The context limit for ChatGPT is measured in “tokens.” A token can be as short as one character or as long as one word. On average, a token is about four characters in English. The limit for GPT-4 is around 8192 tokens, which includes both the prompt and the generated response. This limit encompasses all the text that ChatGPT can consider at one time when generating a response, so it’s important to manage the amount of context provided to ensure that the most relevant information is included within this constraint.
ChatGPT Speech-to-Speech
A simple life hack that moves beyond transcription is live speech-to-speech interaction with ChatCPT. This transcribes the interaction as you go.
It feels like the above makes for ripe opportunity to develop a workflow front end for the iterative process of optimising long-form text.
