Anapoly AI Labs

Author: Alec Fearon

  • A new way of working

    Transparency: AI-assisted (see justification below)

    A reflection on where I have got to after using ChatGPT and other AIs intensively for the past six weeks.

    In earlier times, my digital workspace was built around the usual office applications – Microsoft Office or Google Workspace, and their ilk. Now, it’s different. 

    Microsoft is going down the path of embedding AI (mainly ChatGPT) into its productivity suite. I have taken a different path, choosing to use ChatGPT, Perplexity, and NotebookLM independently. My workspace is now populated by a team of AI assistants, researchers, analysts, editors, and more, sitting alongside the standard office productivity apps.

    Where I would previously have started a piece of work in Word, now I start in a ChatGPT project canvas. During the course of work, I switch between AI team members. ChatGPT is the main thought partner – good at shaping ideas, helping structure prose, pushing back on woolly thinking. The 4o model is an excellent collaborator for many tasks, but if deeper thinking is needed I switch to ChatGPT-o3; the difference is remarkable.  When the flow falters, I’ll hop over to Perplexity: fast, well-cited, useful for breaking through with a different angle or clarifying a half-formed idea. NotebookLM, meanwhile, knows my  files; it acts like a personal librarian, drawing references and insight from the sources I’ve given it.

    It’s not seamless yet. But this is a distinctly new way of working, shaped by interaction between multiple AI agents. Even when ostensibly alone at my desk, the feeling is less of working as a solitary engineer and more as the leader of a team. A quiet, tireless, and always surprisingly helpful team. The skill here is no longer about choosing the best tool. It’s about understanding which kind of tool to use and when – treating each one as if it were a specialist on call.

    This hopping back and forth isn’t distraction, it’s coordination. Each assistant brings a slightly different lens. Triangulating between them often clears a logjam in my thinking or brings up a new insight. An intrguing thought is whether – or perhaps when – they will gain an awareness of each other’s contribution, turning coordination into collaboration.

    For the record, I drafted this post in a ChatGPT project canvas, helped by the AI in a chat alongside the canvas. When complete, I told the AI to write the “transparency label justification” below. It was spot on!

    Transparency Label Justification: This diary post was drafted collaboratively with ChatGPT using the GPT-4o model. Alec described his working patterns in detail and directed the structure and tone throughout. ChatGPT proposed phrasing, clarified distinctions between tools, and refined transitions, but the observations, reflections, and examples are all drawn from Alec’s own practice. The post captures a real and evolving style of AI-supported work, shaped and narrated by its practitioner.

  • Collaboration in ChatGPT?

    transparency label: human only

    There are reports that:

    OpenAI has been quietly developing collaboration features for ChatGPT that would let multiple users work together on documents and chat about projects, a direct assault on Microsoft’s core productivity business. The designs have been in development for nearly a year, with OpenAI’s Canvas feature serving as a first step toward full document collaboration tools.

    Source: The Information via BRXND Dispatch

    This would be a change towards something like simultaneous collaboration with colleagues on a shared document in Microsoft Office. At present, a ChatGPT Team account allows more than one person in the Team account to work in a project space and to take part in the chats within that project, but only one person at a time, as I understand it.

  • First thoughts on a lab framework

    transparency label: Human-only

    A few hours spent with ChatGPT-o3 resulting in good first draft of a framework for thinking about our labs. It covers

    • types of lab
    • the roles of people involved with the labs
    • the core technical configuration of a lab
    • assets needed to launch, operate, and archive a lab
    • a naming convention for these assets

    No doubt the framework will need to be tweaked and added to as our ideas mature.

    The chat with o3 was a valuable mind-clearing exercise for me, and I was impressed by how much more “intellectual” it is compared to the 4o model. Like many intellectuals, it also displayed a lack of common sense on occasions, especially when I asked for simple formatting corrections to the canvas we were editing together. The 4o model is much more agile in that respect.

    During the chat, when the flow with ChatGPT didn’t feel right, I hopped back and forth to consult with Perplexity and NotebookLM. Their outputs provided interestingly and usefully different perspectives that helped to clear the logjam.

    A decision arising from my joint AI consultation process was the choice of Google Workspace for the office productivity suite within our labs. This will allow for much better collaboration when using office tools with personal licences than would be the case with Microsoft Office 365. Given the ad hoc nature of labs and the cost constaints we have, this is an important consideration.

  • Use cases for NotebookLM

    Posting in his SubStack Adjacent Possible, Steven Johnson discusses how “language models are opening new avenues for inquiry in historical research and writing“. He suggests they can act as collaborative tools, rather than replacements for the writer’s engagement with primary sources.

    Johnson argues that NotebookLM is designed to facilitate rather than replace the reading of original sources. I t does so by making the entire source readable within the app, and by provinding inline citations linked directly to the original material.

    He identifies some interesting use cases.

    The AI can be a tool for collaborative brainstorming by allowing users to explore different hypotheses and see patterns within personally curated sources.

    NotebookLM can be used for targeted information retrieval.

    • It can help “fill in blank spots” or remind users of forgotten details from their readings.
    • The tool is valuable for fact-checking against uploaded source material.
    • For specific information, like in a car manual, it can provide direct answers to questions through a conversational Q&A format.

    It can enhance serendipitous discovery by suggesting surprising, less obvious connections amongst the sources.

    It can create mind maps from the sources, in effect indexing them on the fly.

    Finally he speculates on a future where e-books could come with a NotebookLM-like interface. This would bundle together the main work with all the original sources used by the author, enabling “timelines, mind maps, and explanations of key themes, anything you can think to ask”.

  • How ChatGPT helped draft our first acclimatisation lab setup

    Date: 24 June 2025

    transparency label: AI-heavy

    Our latest Lab Note records a quick experiment where I asked two ChatGPT models to draft the outline for an “acclimatisation” session – the starter lab we plan to run with newcomers to AI.

    Highlights:

    • Model face‑off: I ran the same prompt in parallel on model o3 and model 4o. The reasoning‑focused o3 delivered a tight nine‑part outline. 4o wandered off‑piste.
    • Time cost: The branch test took three minutes and gave us a clear winner.
    • Transparency: The Lab Note carries an AI‑heavy label because most of the prose came straight from o3. I trimmed, corrected one hallucination, and signed off.

    If you are curious about our process or want to see how structured prompting keeps the bot on track, read the full note here: First Acclimatisation Session Lab Note →

  • Drafting Anapoly’s first Lab Setup with ChatGPT

    Transparency label: AI‑heavy (ChatGPT model o3 produced primary content; Alec Fearon curated and lightly edited)

    Purpose of experiment

    Use ChatGPT as a thinking partner to create a first draft of an acclimatisation lab setup for Anapoly AI Labs and to compare output quality between two models (o3 and 4o).

    Author and date

    Alec Fearon, 24 June 2025

    Participants

    • Alec Fearon – experiment lead
    • ChatGPT model o3 – reasoning model
    • ChatGPT model 4o – comparison model

    Lab configuration and setup

    Interaction took place entirely in the ChatGPT Document Workbench. The first prompt was duplicated into two branches, each tied to a specific model. All files needed for reference (conceptual framework, lab note structure) were pre‑uploaded in the project space.

    Preamble

    Alec wanted a concise, critical first draft to stimulate team discussion. The exercise also served as a live test of whether o3’s “reasoning” advantage produced materially better drafts than the newer 4o model.

    (more…)

  • No substitute for reading the paper

    transparency label: Human-only

    … what I can say is that a theme throughout this self-analysis is this: I find ChatGPT to be a really useful tool when I already have some idea of what I want to do and when I’m actually engaged with the issue. I find it much less reliable or useful for completely automating parts of the process. There’s no substitute for reading the paper.

    Source: Sean Trott in his newsletter How I use (and don’t use) ChatGPT on 24 June 2025

  • ChatGPT models: which to use when?

    transparency label: Human only

    ChatGPT-4ofast, for brainstorming, quick questions, general chat
    o3powerful, for serious work (analysis, writing, research, coding)
    o3-proultra-powerful, for the hardest problems

    Source: One Useful Thing, Substack newsletter by Ethan Mollick, 23 June 2025

  • That was the moment …

    transparency label: Human only

    It hit me that generative AI is the first kind of technology that can tell you how to use itself. You ask it what to do, and it explains the tool, the technique, the reasoning—it teaches you. And that flipped something for me. It stopped being a support tool and became more like a co-founder.

    A quote from BRXND Dispatch, a SubStack newsletter by Noah Brier, which featured Craig Hepburn, former Chief Digital Officer at Art Basel.

  • Lab Note: modelling our own use of AI tools

    Transparency label: AI-heavy

    Purpose of experiment

    To identify and configure an AI toolkit for Anapoly AI Labs that credibly models the use of general-purpose AI tools in a small consultancy setting.

    Author and date

    Alec Fearon, 24 June 2025

    Participants

    Alec Fearon, with Ray Holland and Dennis Silverwood in email consultation
    ChatGPT-4o

    Lab configuration and setup

    This setup models a real-world micro-consultancy with three collaborators. It assumes limited budget, modest technical support, and a practical orientation. We aim to reflect the toolkit choices we might recommend to participants in Anapoly AI Labs sessions.

    Preamble

    If Anapoly AI Labs is to be a credible venture, we believe it must model the behaviour it explores. That means our own internal work should demonstrate how small teams or sole traders might use AI tools in everyday tasks – writing, research, analysis, and communication – not just talk about it. This lab note outlines our proposed working configuration.

    Procedure

    We identified common functions we ourselves perform (and expect others will want to model), for example:

    • Writing, summarising, and critiquing text
    • Researching topics and checking facts
    • Extracting and organising information from documents
    • Sharing and collaborating on files
    • Managing project knowledge

    We then selected tools that:

    • Are available off the shelf
    • Require no specialist training
    • Are affordable on a small-business budget
    • Can be configured and used transparently

    Findings

    Core Tools Selected

    FunctionToolLicenceNotes
    Writing & promptingChatGPT Team£25–30/m/userMain workspace for drafting, reasoning, editing
    Search & fact-checkingPerplexity Pro$20/m/userFast, source-aware, good for validating facts
    Document interrogationNotebookLMFree (for now)Project libraries, good with PDFs and notes
    Office appsMS 365 or Google£5–15/m/userMatches common small business setups
    Visual inputsChatGPT VisionIncluded with ChatGPTUsed for images, scans, and screenshots

    Discussion of findings

    This configuration balances affordability, realism, and capability. We expect participants in Anapoly AI Labs to have similar access to these tools, or to be able to get it. By using these tools ourselves in Anapoly’s day-to-day running, we:

    • Gain first hand experience to share
    • Create reusable examples from real work
    • Expose gaps, workarounds, and lessons worth documenting

    We considered whether personal licences could be shared during lab sessions. Technically, they can’t: individual ChatGPT and Perplexity licences are for single-user use. While enforcement is unlikely, we’ve chosen to adopt the position that participants should bring their own their own AI tools – free or paid – to lab sessions as part of the learning experience. This avoids ambiguity about licencing and sets the ethical standard we want to maintain.

    Conclusions

    This toolkit would enable us to model our own small-business operations, treating Anapoly itself as one of the lab setups. That would reinforce our stance: we don’t claim to be AI experts; we’re practitioners asking the questions small businesses wish they had time to ask, and showing what happens when you do.

    Recommendations

    • Configure project workspaces in ChatGPT Team to reflect different lab contexts
    • Maintain prompt libraries and reasoning trails
    • Make costs, configurations, and limitations explicit in diary and lab notes
    • Evaluate whether to add AI-enhanced spreadsheet or knowledge tools (e.g. Notion, Obsidian) in future iterations

    Tags

    ai tools, toolkit, configuration, modelling, small business, chatgpt, perplexity, notebooklm, office software, credibility

    Glossary

    ChatGPT Team – OpenAI’s paid workspace version of ChatGPT, allowing collaboration, custom GPTs, and project folders.
    NotebookLM – A Google tool for working with uploaded documents using AI, currently free.
    Perplexity Pro – A subscription AI assistant known for showing sources.
    Vision input – The ability to upload images (photos, scans) and have the AI interpret them.