Platform Engineering

The pain

You probably landed on this page because one of these sounds familiar:

• The internal platform team has 4 people serving 60 product engineers. The ticket queue grows faster than the capacity to resolve it.
• Production deploys take 6 weeks and each release needs 3 coordination meetings. Managers no longer ask “when does it ship” because the honest answer hurts morale.
• There’s observability but nobody correlates costs with real usage or with contracts. The CFO asks “explain why the Datadog bill went up 40%” and the honest answer is “we don’t know.”
• Compliance asks for traceability of who deployed what and when. The team has the logs but doesn’t correlate them with tickets or changes. Each audit consumes two weeks of a staff engineer.
• There’s a purchased IDP or an internal platform-as-product project that’s been running 18 months and still isn’t in production.

None of these is a tooling problem. It’s a problem of platform without opinionatedness — no clear decision on what’s offered, what’s forbidden, and who owns each layer.

What CultureTech prepares

A Staff Engineer embedded with the client team for 3-6 months, focused on one of these domains (not all five at once):

• Opinionated Internal Developer Platform — Backstage or equivalent custom build, with a real service catalog, maturity scoring, and golden paths for the 3-5 service types the organization actually builds. Not “platform that does everything” — platform that covers 80% of cases quickly.
• FinOps with cause-and-effect — crossing technical observability with cost attribution. The output: how much it costs to serve each feature, each customer, each query. With that, retirement or redesign decisions stop being political.
• SRE with auditable SLOs — burn rate alerting, error budgets that are actually respected, postmortems with reconstructed timeline. In regulated banking this translates into evidence for CMF and equivalent regulators.
• Semantic observability — via Aether Telemetry (lab product). The change versus traditional OTel: each trace, metric or log carries contractual context (which SLA, which customer, which tier). Enables detecting drift between what the contract says and what the service delivers, not just p99 latency.
• GitOps + IaC with chain of custody — every infra change goes through git, every merge ships with cryptographic signature, every deploy ships with SLSA L3 or L4 attestation. Applies especially to Kubernetes and sensitive workloads.

The engagement doesn’t deliver slideware or “strategy.” It delivers code in your repo, dashboards in your Grafana, runbooks in your wiki, and your team operating it all.

Who it’s for

• Organizations with more than 50 engineers and an existing internal platform team (3 to 10 people) that needs senior capacity to unblock or redirect.
• Sectors where regulation crosses with velocity — banking, healthcare, telco, GovTech. The service treats compliance as a hard constraint, not a decorative layer.
• CTOs/VPEs who recognize the problem isn’t solved by hiring 3 more mid-level engineers, but with a short, focused senior intervention.

What it’s not

• Body shop with junior pricing-by-the-hour. The engagement is senior capacity focused on outcome, not hours sold.
• Consulting with a Word deliverable. If what we deliver doesn’t compile, we didn’t deliver.
• “Digital strategy.” Others do that, better.
• Replacement for the internal platform team. It’s an accelerator. The client team operates what was built when the engagement closes — no lock-in, no mandatory retainer.

How it crosses the portfolio

• Aether Telemetry — the semantic observability layer that instruments platform engineering when the client adopts the lab product. It’s the piece that differentiates the result vs a platform team only operating OTel.
• Themis — AIOps SRE agents that consume Aether signals to automate runbooks. Applies in late engagement phases, once SLOs are established.
• OTel Strangler Fig — the OpenTelemetry migration playbook without big-bang we use as base approach when the organization has fragmented legacy observability.
• Agentic SRE — pattern for introducing AI agents into the SRE cycle without losing operational rigor.

When it activates

Q3 2026. Before that, the engagement is blocked by Thoth’s SII certification and the operational dedication needed to serve the first real client. The pre-conversation is open — booking discovery doesn’t commit to work start, but it does let you align scope and expectations in advance.

The process: discovery week (no cost) → proposal with scope limited to one domain → 3-6 month engagement → documented handoff. No mandatory post-engagement retainer.