On the Stack…
Bitter Lesson, Rich Sutton, 2019
It's bitter because the lesson keeps getting re-taught. Attempts to embed our interpretation of discovery and understanding into AI are quickly surpassed in performance by generalized approaches to search and learning with increased computing power. Otherwise summarized: "the only thing that matters in the long run is the leveraging of computation". In the field of finance and accounting, where we have a tendency to hold in high esteem the contribution of human experience, I wonder how this'll play out in application of AI and agentic AI. It's compelling (and comforting) to think our current methods and processes contain permanent value, but maybe it's all rather irrelevant in the not too distant future? In which case, our current problem solving approaches aren’t useful in training models, but our ongoing interactions are critical for inference.Roadmap: AI systems of action, Bessemer Venture Partners, 2025
An important thread in the disruption of legacy ERP is the application of AI to the implementation process, which "means the time and cost to move to a new system are significantly less." This has big (ooh, huge) potential: Current incumbents' moats rely upon high switching costs, remove that and you have a much more open playing field. And not to mention the increased ease of building features in platforms using AI, this means—as I think has been said most succinctly by Franz Farber of Everest Systems—the true value of platforms will be in the guarantee of an outcome (which is really the value the customer actually needs), e.g. a guarantee your financials are accurate and you will be audit ready…Future of Work with AI Agents, Stanford University, 2025
"Domain workers want automation for low-value and repetitive tasks." People naturally want to spend less time doing the boring stuff and it means more time is available for higher-value work, which should result in higher profit margins. Win-win all around then.
Though I wonder: Sometimes we enjoy not having to turn our brains on, especially the morning after the night before... do we switch AI off at that point?
The paper also highlights the three most prominent concerns about AI:
1. lack of trust in accuracy
2. fear of job replacement
3. absence of human qualities or capabilities (see above and the Bitter Lesson)
Then in conclusion "From an incentive perspective, some workers may also withhold honest feedback due to concerns about job security or surveillance." Key takeaway for executives in companies investing in AI usage—bring the team along and focus on reskilling, they are part of the solution not a consequence of it.How CFOs are navigating growth, pricing, and forecasting in an AI world, a16z, July 2025
Annual subscription licenses and revenue recognition often mask the underlying business health—customers may not even be using the platform, but yet the P&L shows revenue recognition on an amortized basis. This happens more often than you'd think. Consumption based pricing (and consequently revenue recognition) would better tie reported financial performance to actual customer value delivered. Finance processes to efficiently implement this have to depend on automation.
Approaches to ARR then need refined to include annualized estimates of consumption revenue. And then there’s margin: Optimizing margin in operations becomes a fine-grain task of managing costs with usage, requiring clarity on financial impact on a much shorter timeframe than usual month close cycles. Systems need to reliably link activity to predicted financial consequences so optimizations can be made throughout each month.I agree with this: "You can't achieve the precision required in consumption forecasting using Microsoft Excel — you have to use advanced analytics, machine learning, and AI to build those predictions."
But, the unending flexibility of Excel is going to be very difficult to unseat as the principle work medium for finance, FP&A etc. It's a question in the nearer term then of how Excel is augmented (time to highlight Aleph as a key player) by the increased ease of data access and all that brings to the challenge. And then we're into how AI can help make sense of that data—will be fascinating to see how interfaces will evolve to enable natural language direction.
Blub's Paradox in Finance, Looks Gerat!, March 2025
Great perspective on why Excel users tend to stick with Excel. Before LLMs and the advent of easy code generation it took a lot more brain power and time commitment to wrangle Python for data processing, Now it's remarkably easy to craft up a script for manipulating and visualizing data—training LLMs benefits from copious amounts of Python code in the ether and so the resulting models can produce pretty useful code straight off the bat. However, even though complex Excel formulae represent many coding constructs (and so Excel power users should be able to pick up more powerful languages) the whole environment of coding is vastly different to that of spreadsheets. Yes, stuff like version control becomes a built-in feature rather than hacked using filenames, but the user needs to build familiarity with projects, libraries, version control and repos, managing virtual environments, not to mention unit testing—which is snother of the massive benefits of coding vs spreadsheets--and so on to actually access the power. I'm a big proponent of moving large portions of what we deal with in financial projections, modeling and analysis to coding—it's just that the complexity of doing that and maintaining reliability and integrity in the output shouldn't be underestimated.
In the Glass…
Glen Scotia 7 Year, 1st Fill Ruby Port Hogshead
Exclusive cask, bottled for Loch Fyne Whiskies
Picked this up on a recent trip back home, from Loch Fyne Whiskies in Inverary, an almost guaranteed stop for me on the drive west. Glen Scotia is one of my absolute favourite distilleries and I never fail to enjoy what they release (code #93 with SMWS by the way, and I have a few of those bottles). The exclusives that LFW get are always excellent and sell out very quickly. This one is no different, the port notes clear and distinct, and the slight smoke that just trickles through on the palate. Terrific stuff.
Last Thought…
I used em dashes long before ChatGPT got into the game but I take no responsibility for correct or incorrect usage, or indeed for the mixed up British vs US spelling above. However, I do strongly recommend checking out ellecordova’s Instagram for some fun with grammar and planets.