Method
Editorial log
Every published page on this site, who reviewed it, when, and what the review changed.
Scaled content is penalised when it is published without review. Rather than assert that review happens, the record is kept here and the build will not publish a page whose review block is missing or dated before the page was written.
One collection is reviewed differently and the table says so rather than hiding it. Market pages carry no third-party figure — every publishable fact on one is a named authority, a section number, an institution or a link — so each is checked by retrieving the source and searching it, and the URL, the status, the hash and the matched passage are recorded. A field that cannot be established that way is dropped; a page whose required fields cannot be is not published. Everything that carries a figure somebody else measured is still read by a person before it ships.
| Page | Type | Reviewed by | Reviewed | What the review changed |
|---|---|---|---|---|
| What does AI do badly that people assume it does well? | Answer | Answer Production Engine | 2026-08-25 | Removed long tasks and general accuracy from the draft's list, since both are failures of structure and supplied material rather than of the system, and leaving them in would send readers to the wrong fix. Added absence detection, which is the most consequential of the four in real work and appears on no conventional list. |
| What does it mean to give an AI agent access to your computer or business systems? | Answer | Answer Production Engine | 2026-08-25 | The draft's central recommendation was a careful prompt describing what the agent should not touch. That is instruction where a permission is required, and the page now says so directly. Added the disclosure paragraph after checking how tool results reach the provider, which is the part readers most often get wrong. |
| What does reliable mean for an AI system? | Answer | Answer Production Engine | 2026-08-25 | Added consistency as a fourth property after noticing that the three engineering requirements do not capture what people describe when they say a system is unreliable. Cut a comparison with human error rates, which is rhetorically attractive and not a like-for-like comparison, since human errors are distributed and detected differently. |
| What happens to your skills when AI does the work? | Answer | Answer Production Engine | 2026-08-25 | Added the experienced-practitioner case, which the draft folded into the junior one and which has a different mechanism: the judgement exists and drifts rather than never forming. Also added the erosion of the checking habit, which affects everyone reviewing generated work and is the most immediate version of the problem. |
| What happens to an AI automation when the person who built it leaves? | Answer | Answer Production Engine | 2026-08-25 | Added the personal-infrastructure point, which the draft treated as a documentation problem. It is a distinct failure that documentation cannot address, and it is the more common one in small businesses. Also added the rebuild-while-running recommendation, since the working automation is the only complete specification that will ever exist. |
| What happens when an AI agent has too much context? | Answer | Answer Production Engine | 2026-08-25 | The draft described the effect as slower and more expensive, which is the intuitive account and is not what is observed. Rewritten around the symptoms that actually appear. Added the recency effect as a separate mechanism, since a page attributing everything to volume would misdirect anyone whose session is long rather than large. |
| What is a good first agent workflow for a business? | Answer | Answer Production Engine | 2026-08-25 | Added the requirement that the output be something already wanted, which the draft omitted. A read-only daily workflow whose report nobody opens satisfies the other two criteria and teaches nothing, and that is the most common way a sensible first project produces no information. |
| What is context engineering? | Answer | Answer Production Engine | 2026-08-25 | The draft listed the four techniques as best practice. Added the losses each one carries, because presenting them as free improvements is how teams adopt compaction and then cannot explain why a detail disappeared. Cut a definition-of-terms section that restated the same distinction three ways. |
| What is MCP and why would a business use it? | Answer | Answer Production Engine | 2026-08-25 | The draft explained the protocol's message flow in detail, which dates quickly and serves nobody making a business decision. Replaced with the three properties that survive version changes. Added the tool-crowding cost, which is absent from vendor material and is the problem readers hit second. |
| What is an AI agent? | Answer | Answer Production Engine | 2026-08-25 | The first draft defined the term and stopped, which would have made this a dictionary entry competing with several thousand of them. Replaced the second half with the two things a reader actually needs next: why the definition predicts the failure mode, and the whiteboard test for whether they need one at all. Cut a paragraph on model capability that implied agent reliability tracks model strength, which the evidence does not support. |
| What is the difference between an AI chatbot and an AI agent? | Answer | Answer Production Engine | 2026-08-25 | Removed a comparison table from the draft. The two categories differ on one axis and a table of six rows would have implied five more distinctions than exist, which is the padding this page type is meant to avoid. Added the cost-shape paragraph after checking that the retry behaviour is the first thing operators actually cap. |
| What is the difference between retrieval and verification? | Answer | Answer Production Engine | 2026-08-25 | Added the evaluation consequence, which the draft omitted. Without it a reader could accept the distinction and continue measuring retrieval quality, which is the specific way this failure survives in systems whose owners have read about it. Also added the closing paragraph so the page is not read as an argument against grounding. |
| What is the difference between AI automation and an AI agent? | Answer | Answer Production Engine | 2026-08-25 | Added the closing qualifier after the draft implied that model steps are the fragile part of an automation. In practice the fragile part is the missing branch for the uncertain case, and letting the wrong implication stand would have pointed readers at the wrong fix. Also cut a cost example with invented figures. |
| What makes a long-running AI job fail? | Answer | Answer Production Engine | 2026-08-25 | The draft was about drift and context degradation, which already has its own page and is not what stops long jobs. Rewritten around operational causes after considering what the final log entry of a failed run actually says. Added disk accumulation, which produces the most confusing symptoms of any cause here. |
| What makes an AI agent unreliable? | Answer | Answer Production Engine | 2026-08-25 | Added the closing section on genuine non-determinism. Without it the page claimed setup accounts for all unreliability, which is not true and would have set readers up to conclude the advice failed the first time a well-configured run varied. Cut a comparison of model capabilities, which dates immediately and is not the subject. |
| What makes an AI answer worth acting on? | Answer | Answer Production Engine | 2026-08-25 | Cut a list of quality signals to look for in an answer. Every item on it was a property of the writing rather than of the finding, which is the mistake the page exists to correct. Replaced with the two-axis test, which produces a handling for each case rather than an impression. |
| What should a beginner use AI for first? | Answer | Answer Production Engine | 2026-08-25 | The draft opened with a list of starter use cases, which is the shape of every article on this question and answers a different question than the one asked. Rewrote around the selection criterion instead. Added the closing warning against early automation after noting that the rest of the page depends on the reader seeing every output. |
| What should a law firm never let AI do? | Answer | Answer Production Engine | 2026-08-25 | Checked the closed-system question against the published opinion rather than assuming, and the guidance goes the other way from the common assumption, so the page states it explicitly. Added the billing point, which is a professional issue firms create for themselves and which no technology discussion raises. |
| What should a manufacturer check before connecting AI to production systems? | Answer | Answer Production Engine | 2026-08-25 | Added behaviour under connection loss, which the draft omitted and which is the check that turns a routine outage into a production incident. Also separated predictive maintenance into the honest answer about data availability, since a proposal built on sensor history a small manufacturer does not have is the most common wasted project in this area. |
| What should a real estate agent never automate? | Answer | Answer Production Engine | 2026-08-25 | Made the fair housing section the centre of the page rather than one item among several. Generated property copy drifts into the constrained formulations by default because it is imitating the convention, which means the exposure arrives without anyone choosing it, and that is the finding an agent needs before publishing anything. |
| What should a small business do when staff are already using AI? | Answer | Answer Production Engine | 2026-08-25 | The draft opened with writing a policy. Moved that to fourth after establishing that a policy written against assumptions bans the wrong things and drives the rest out of sight, which is the outcome most businesses reach. Added the opportunity-assessment point, which turns the discovery conversation into something with a return rather than a control exercise. |
| What should an agent report when it finishes? | Answer | Answer Production Engine | 2026-08-25 | Cut a report template and replaced it with the four items and the reason each is there, because a template gets filled in while the reasoning determines whether the filled-in version is worth reading. Added the length rule, which also diagnoses a run that should have been divided. |
| What should an agent write down and what should it look up? | Answer | Answer Production Engine | 2026-08-25 | Added the derived-summary case. The draft's binary rule sent expensive analyses to be recomputed every time, which nobody does, so the page would have been ignored at exactly the point it was most needed. Also sharpened the definition of written down, since the draft's advice is inert if a session note counts. |
| What should an AI agent do when a tool call fails? | Answer | Answer Production Engine | 2026-08-25 | Added the third class — the successful call with an unusable payload — after noticing the draft's two-class scheme leaves a common failure entirely unhandled. Also added the note on post-failure improvisation defeating a permission, which is the security consequence of retry guidance and was absent from the draft. |
| What should an AI regression test look like? | Answer | Answer Production Engine | 2026-08-25 | Added the ambiguity of failure, which distinguishes this from ordinary regression testing more than anything else on the page and determines the response. Also promoted exclusion assertions from a passing mention, since they are the highest-consequence tests and the ones teams consistently do not write. |
What the build refuses to publish.
Four checks run before any page in this system is generated, and each one stops the build rather than producing a warning nobody reads.
A page must name, in writing, what is on it that could not appear unchanged on a sibling page — and no two pages may give the same answer. Independently of that, every page is reduced to a fingerprint with its own subject and place names masked out; if two fingerprints match, or come close, both pages are named and the build stops. That is the check that catches a page whose only distinguishing feature was the city in the heading.
A page must also carry at least two datapoints that are specific to its own subject rather than to its category, and if the same figure is claimed as specific on two different pages, it was specific to neither. Pages ship in cohorts with a size cap so indexation can be observed between them, and every page carries the review block that produces the table above.
All four are properties of the schema, not of anyone remembering. Reviewed by Siddharth Sharma, except the 0 market page(s) above, which are checked against their sources and carry the record of it.
GATES
A gate enforced by a person reading pages stops being enforced somewhere around page 60.