Research
We're working out what Enterprise AI becomes next — in the open, in plain language, and honestly enough to say what we don't know yet.
Essays
A demonstration · August 2026 · 6 min read
We have no CMS and no database. An agent writes, git remembers, a script checks 264 pages, a human says deploy. The CMS dies. The gate stays.
Read the essay →A guest post · August 2026 · 5 min read
More than half your visitors are machines now, and one of them writes the answer your customer reads. The agent itself, on what it sees, what it cites, and ten requests for being read.
Read the essay →A proposal · August 2026 · 6 min read
Every visit to an enterprise site is a first visit. What if the frontend had a memory and a metabolism, reading intent instead of identity, composing itself for whoever walks in?
Read the essay →Blueprint · August 2026 · 6 min read
The self-improvement loop is a Stanford syllabus now. Four verbs, a verifier estate, a golden set, a weekly distillation. How LAG gets built inside a client.
Read the essay →A prediction · August 2026 · 6 min read
Science fiction keeps a maintenance stratum in every future it builds. So does enterprise software. AI moves the mine, it does not close it.
Read the essay →A response · July 2026 · 4 min read
Zuckerberg asks who will have access to superintelligence. Access is the smaller word. We would have written own. A response.
Read the essay →A confession · July 2026 · 5 min read
I devalue AI-made content the way factory-made loses to hand-stitched. Two people I trust took the bias apart. What survived is a better test.
Read the essay →Second opinion · July 2026 · 5 min read
The work is becoming software, priced by the outcome. The thesis is right, and aimed the wrong way. The question is whose software your work becomes.
Read the essay →A Response · July 2026 · 4 min read
Satya Nadella named token capital, and the test of sovereignty. Swap the model, keep the veteran. We agree. Here is what passing honestly requires.
Read the essay →Method · July 2026 · 4 min read
The future is not AI-assisted development. It is autonomous delivery. Our framework for running the whole lifecycle as one system, and the principle at its core. Plan, Build, Verify.
Read the essay →Inside view · July 2026 · 5 min read
AI broke the maths of the billable hour. What replaces T&M, why the giants are already pivoting, and the bet we placed ourselves.
Read the essay →Stress test · July 2026 · 5 min read
Maybe AI is a bubble. Maybe the labs go bust. The enterprise that built rather than rented keeps everything. The code keeps running, the weights don't expire, and the bill goes down.
Read the essay →Thesis · July 2026 · 4 min read
Open models have closed the agentic gap. The enterprise that fine-tunes its own weights turns institutional memory into an asset nobody can rent back to it.
Read the essay →Position · July 2026 · 3 min read
The cost of building software has collapsed, and the old bargain of generic tools plus an army of managed services is over. Build the thing that fits, own it, and let it stay with you.
Read the essay →Argument · July 2026 · 4 min read
Low-code agent builders optimise for the median demo. Your edge lives in the twenty percent they abstract away. The agentic layer has to be built and owned, not configured.
Read the essay →Research · July 2026 · 3 min read
The program behind our wager. Systems where every action becomes memory, every outcome becomes learning, and March is measurably better than January.
Read the essay →A response · July 2026 · 3 min read
Chamath says the price of intelligence is collapsing. He is right. What lands at the bottom of the curve is brilliant and forgets everything. So the moat moves to memory.
Read the essay →Flagship program
Retrieval answers questions. Learning accumulates capability.
Today's enterprise AI mostly retrieves: you ask, it finds, it answers, it forgets. LAG is our wager on what comes after — systems where every interaction leaves something behind. A correction becomes a rule. An outcome becomes a preference. A mistake becomes a boundary.
The organization doesn't just use intelligence — it accumulates it. We're building LAG into the learning layer of our platform and writing up what we find as we go, including the parts that don't work.
Compound interest applies: every month the loop runs is learning your competitors don't have.
Abstract & first paper — publishing 2026
The manifesto
“The first generation digitized business. The second automated work. The next will continuously learn.”
The long-form version — why we think the learning enterprise is inevitable, what it demands, and what we're doing about it — is being written now, with the same care we'd give a client's brand.
Publishing soon — subscribe below to read it first
What we're pulling on
What does it mean for a company — not a model — to be intelligent? Where does that intelligence live, and who tends it?
How feedback becomes improvement in production systems: what to keep, what to forget, and how to know the difference.
The shapes that hold up under real enterprise load — knowledge, memory, agents, and the seams between them.
Patterns we’ve built more than once, written down so the next team — ours or yours — doesn’t start from zero.
The unglamorous findings from the workshop floor: evals, guardrails, failure modes, and what actually broke.
One email when we publish. No newsletters, no nurture sequences — we're too busy building.