Documenting Engineering Decisions: Notion or Slite

An architecture decision record, why you chose a message queue over polling, why a client's data residency requirement ruled out a particular vendor, is only useful months later if the reasoning is still attached. Notion's linked databases let you connect a decision record to the client project, the engineer who made the call, and any later record that reversed it, which is genuinely useful when a new hire asks why the codebase does something unusual.

Slite doesn't offer that relational linking, but it does something Notion doesn't: it flags when a decision record hasn't been reconfirmed. For a fast-moving custom shop juggling several client codebases, an architecture decision that's two years stale and never revisited is a real risk, since the constraint that justified it may no longer exist.

Custom software shops churn engineers between projects more than product companies do, which makes onboarding documentation a recurring cost rather than a one-time setup. Notion's database views let you build a single onboarding hub filtered by client or by tech stack, so a new engineer sees only what's relevant to their assignment.

Slite's advantage shows up once that engineer starts asking questions. Ask AI answers from verified docs and cites its source, which beats sending a new hire to search a wiki where half the results are two client migrations out of date.

It's easy for a page written for one client's peculiar deployment pipeline to get treated as the company standard, especially in Notion's single flexible workspace where everything looks the same at a glance. Deliberately separating client-scoped databases from company-wide process databases, and naming them so the distinction is obvious, avoids a new engineer copying a one-off workaround into a project where it doesn't apply.

Slite's structure of separate channels for separate audiences makes that separation slightly more natural by default, though it still requires someone to decide up front what belongs where.

R&D spend runs at a median of 22% of ARR at private B2B SaaS companies¹, and a custom software shop's version of that spend is engineering hours, many of which go to relearning decisions that were already made once. CAC payback across the sector sits at a 16-month median², which leaves little room for an engineering org that's slow to ramp new hires because the history lives only in someone's memory.

The operations or delivery lead who owns this problem, at a median salary of $105,770³, is usually the person who ends up mediating between client-specific chaos and company-wide standards.

The shops that handle this well tend to separate three layers: a durable company handbook (hiring, security policy, coding standards), a client-specific project hub per engagement, and an architecture decision log that links the two. Which platform holds which layer matters less than making the separation explicit and reviewable.

If you're also comparing a third documentation platform for this decision, see where Confluence fits against both.

A documentation structure that survives staff turnover has these layers:

• A durable company handbook covering hiring, security policy and coding standards that apply regardless of client.
• One client specific project hub per engagement to hold that client's technical history.
• An architecture decision log that links the two and keeps the reasoning attached to each decision.
• Client scoped databases named and kept separate from company wide process databases, so one client's pipeline is not mistaken for the standard.
• Decision records stored in a separate linked log so the reasoning survives after an engagement's workspace is archived.

Engineers sometimes try to make a documentation platform behave like a codebase, endless revision comments, a full edit history nobody reads, contradictory notes left in place because deleting them feels like losing information. That instinct is understandable and usually counterproductive. A wiki page isn't a commit log. Its job is to state the current truth clearly, not to preserve every past belief about the topic.

The related mistake is the opposite one: copying a single client project's README wholesale into the company-wide handbook because it happened to be well-written. A README written for one client's specific deployment pipeline carries assumptions, a particular cloud provider, a particular CI setup, that don't hold for the next client, and a new engineer who trusts it as general guidance will build the wrong thing. The instinct to reuse good writing is right. The mistake is reusing it without stripping out what's client-specific first.

Both mistakes come from the same root cause: nobody decided what a page is supposed to do before writing it. A decision record should show current reasoning, with old reasoning explicitly marked superseded rather than deleted or left ambiguous. A handbook page should state a company-wide default, with any client-specific exception documented separately and clearly labeled as an exception. Get that distinction wrong and even a well-organized Notion workspace or a fully verified Slite wiki ends up misleading the next engineer who reads it.