Been using the Claude Excel plugin for a week and I genuinely didn’t expect it to hit this hard
Why I picked this
Victor's question lands hard: what happens when the augmentation becomes full automation? This practitioner just collapsed five days of financial modeling work into one day using Claude's Excel plugin — not by doing the work for them, but by becoming a debugging partner that actually understands circular references and cross-sheet dependencies. The productivity gain is real and measured. But here's the uncomfortable part: they're still constructing the sheets, still making the strategic choices about what to model. The tool is a spectacular co-pilot. The next step Victor's pointing at — where Claude builds the entire model from a prompt — feels both inevitable and destabilizing. We're watching the last mile of human-in-the-loop knowledge work, and it's compressing faster than anyone expected. The practitioner didn't expect it to 'hit this hard.' Neither did most of us.
Three lenses
I'd be prototyping the agentic version this weekend — prompt-to-model pipeline with validation loops. The hard part isn't generation, it's knowing when the model is actually correct, which is exactly what this practitioner still provides.
Five days to one day is a 400% productivity gain on complex deliverables. If my analysts can produce models this fast without quality degradation, I'm rethinking headcount plans and what 'senior analyst' even means in 18 months.
Everyone's celebrating the speed gain. Nobody's talking about the new failure mode: analysts who can't build models from scratch anymore, completely dependent on a tool they don't understand when it hallucinates a formula.
Companies
Key metrics
- •5 days reduced to 1 day
Why this matters for operators: Operators need to map which knowledge work tasks are in this augmentation zone now versus full automation in 12 months — the transition window is shorter than planning cycles.
I cover AI×GTM intelligence like this every Wednesday.
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Why It’s So Hard for Older B2B Leaders to Compete in AI: Your Customers Can Do A Lot in Claude for $20-$200/Month. And You’re Paying $1.00 Per API Call For the Good Stuff.
- B2B vendors face brutal unit economics: complex AI features cost $0.50-$2.25+ per API call while customers get unlimited access to same models for $20-200/month via Claude direct
- The pricing arbitrage creates existential threat to B2B AI wrappers - customers can increasingly do sophisticated analysis directly in Claude rather than through enterprise software
- Cheap AI features (pennies per customer) signal lack of competitive differentiation - genuinely valuable AI analysis requires expensive extended thinking modes and large context windows that compress margins
Confessions of an AI lab rat
- CEO-level AI adoption requires 1-2 hours daily commitment with disciplined feedback loops - casual usage produces unimpressive results that cause people to dismiss the technology prematurely
- Contrarian shift from 'subtraction story' (cost cuts/headcount reduction) to 'addition story' (3 new revenue lines economically impossible pre-AI) - suggests AI's bigger impact is enabling new business models rather than pure efficiency
- Critical deployment gap: AI capabilities exceed enterprise readiness due to security, system integration, and data access governance issues - agent-to-agent workflows exacerbate this problem at scale
Father of the iPod and iPhone on building taste, judgment, and creativity in the AI era | Tony Fadell
- Cognitive surrender to AI is the biggest risk facing product builders - legendary hardware/software creator warns against over-reliance on AI tools that erode taste and judgment
- Opinion-based decisions are essential for v1 products - data-driven approaches fail when building truly novel products (iPhone keyboard debate as case study)
- AI-generated code creates brittle, unmaintainable products - contrarian take from someone with 300+ patents on why AI coding tools may harm long-term product quality
This analysis was produced using the STEEPWORKS system — the same agents, skills, and knowledge architecture available in the GrowthOS package.