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July 8, 2026

The tech stack of the future for strategy and finance teams.

A five-layer view of how teams will work with agents, warehouses, and LLMs. And where the bottlenecks move.

Five-layer tech stack for strategy and finance teams: storage, context, LLM, charting, and reporting

For twenty years, the strategy and finance playbook was boring in the best way. Warehouse, spreadsheet, deck, ship it.

I do not think that pipeline survives intact. Not because spreadsheets or slide decks go away. Because the path from production data to a decision is splitting into loops. Ask a question. Re-query. Regenerate. Push to a deck. Get feedback. Go back. Same insight, more surfaces.

The teams I talk to are also starting to work with agents that query live data. That only works if the stack underneath is structured. Here is the five-layer model I keep coming back to. Full disclosure: I build charting software.

The five layers

Storage. Production data in a governed warehouse. This layer is largely solved. The open question is access, not location.

Context. A semantic layer between the warehouse and everything upstream. Defined metrics. Approved dimensions. Row-level security. Business language on top of raw tables. Agents need this to query safely and get the same answer twice.

LLM. Where the daily workflow moves. You describe the question. The model pulls data, interprets it, drafts narrative, maybe renders a first pass. Human judgment still matters. The starting point is a conversation, not a blank grid.

Charting. Turn AI output into live, editable charts that travel across surfaces. Power-user control. Data attached. Fit for recurring reporting. Chartbuddy is what we are building for this layer.

Reporting. Distribution stays fragmented. Board decks. Dashboards for monitoring. Written memos. Agent-generated briefs you review and send. The stack has to support multiple endpoints from the same analysis.

What actually goes away

Not spreadsheets. Not decks. The glue work. Rebuilding the same monthly pack from scratch. Screenshotting a dashboard tile and reformatting it. Waiting on a pull an agent could run in minutes. Pasting chart images with no data behind them.

What stays is the human part. Judgment. Narrative. Knowing which number matters this quarter.

A quarter-close in practice

Data in the warehouse. Metrics defined in the semantic layer. An agent pulls a revenue bridge and flags anomalies. Charts get finalized and land in the board pack. A trimmed version feeds a dashboard for monthly monitoring. Same numbers, three surfaces. That loop is the workflow, not the exception.

What I am not sure about

Timing and winners, mostly. Semantic layers will consolidate. Some teams will skip dashboards for ad-hoc work once agents are good enough. Memos might eat more of the board pack than decks. Maybe. Document-first reporting would not be ideal if you sell charting software. You win some, you lose some.

What seems harder to argue with: agents need a governed context layer above the warehouse. And if your deliverable is still a chart-heavy deck, a static image from chat is not a long-term answer.

The useful question

Not "which AI tool should we buy?" but "where does insight still die between the warehouse and the stakeholder?" For most teams I talk to, the answer has not moved much. The data is fine. The last mile of the report is where time goes.

If you are mapping the same transition today, this piece on fragmented FP&A workflows is a useful companion read.

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