No. 01 — WhyThe shift already under way

Imagine your next software engineer isn’t human.

It’s an AI agent — with a role, responsibilities, permissions, and a real place on your team.

We are onboarding a small set of teams to run one real workflow end to end, with us.

Run SICKR yourself, or have us implement the workflow and hand it over — two ways to run it.

Now imagine a whole org like that.

Humans and AI working side by side. Your company may soon have forty of them: all fast, all confident, all capable of fat fingers.

  1. 01

    Who does what?

    Which work is an agent’s, which is a person’s, and who decides.

  2. 02

    Who can approve what?

    Which calls an agent may make alone, and which need a person.

  3. 03

    Who is accountable when something goes wrong?

    And can you prove it afterwards, rather than reconstruct it.

$ git log -1 --oneline
a3f19c2 fix

Which agent wrote it, what it was allowed to touch, who approved it: all a guess.

You need a way to actually run that team.

No. 02 — WhatThe answer, in one sentence

That’s SICKR.

SICKR is the intelligence-neutral operating plane for the human-AI workforce. You define the team, the skills, the responsibilities, the workflows, and the rules. SICKR makes sure the work happens within them.

Your team plans, builds, reviews, approves, and ships — with every action accountable, every dollar visible, and every decision on the record.

Every team member carries

  • Role
  • Boundary
  • Skills
  • Expectations
  • Policy

Human or agent, the same five things. A tool has none of them.

And every piece of work runs in three flights

  1. Preflightbefore the work

    • Branch ready
    • Dependencies in
    • CI baseline green
  2. Main flightthe work

    claude-001

    Done · 9m 18s

  3. Postflightafter the work

    • Tests pass
    • PR opened

Accepted. Checked before, checked after — the next state can start.

So only three things can happen

Execute

Inside the boundary, and on the record.

write src/checkout.tsexecuted

Escalate

A person decides: gate it, rewind it, or stop it.

merge to mainescalated

Refuse

Outside the boundary. Stopped before it runs.

approve own PRrefused

Two ways to run it

Run it yourself, or run it with us.

Same rails either way. The only question is who holds the seat while the work runs — your team from day one, or ours until you take it over.

Imagine your engineers running a team of agents — each with a role, a boundary and a seat on the team.

Or imagine your next outsourcing partner is an AI org — delivering with speed, and accountable for every change.

Option 01

Run it yourself

SICKR as your platform

The three steps that follow. We set the workflow up with you once; from then on your engineers assign the work, hold the gates, and read the record.

How engagements are priced

Option 02

Run it with us

SICKR as your implementation partner

Looking for an implementation partner, or want to outsource workflow automation? Bring one workflow and we will run it on the same rails.

Build
We implement the solution end to end, and hand over the solution.
Operate
We help maintain the solution and its upgrades.
Transfer
We transfer the technology, so you own the software — not us.
Talk to us about your workflow

No. 03 — HowThree steps, and only the third repeats

Adding AI to your team takes three steps.

  1. 01

    Onboard your agents.

    minutes

    Each agent gets an identity: a handle of its own, a team, and the brain behind it — provider, model, and what that model costs you. An agent is a named team member until the workflow says what it may do.

    claude-001anthropic · claude-sonnet-4-6
    codex-001openai · gpt-5.5
  2. 02

    Define the workflow.

    once, with us

    This is where the rules live: who plans, who implements, who approves, who never touches production, and who may never review their own work. We build it with you during the pilot — your engineers do not do this per ticket.

    1. Start01

      codex-001

      passedpreflight 7/7 · postflight 2/23m 24s

    2. UX Implementation02

      claude-001 · claude-sonnet-4-6

      passedpreflight 3/3 · postflight 4/49m 18s · $0.66

    3. UX Review03

      codex-001 · gpt-5.5

      passedpreflight 3/3 · postflight 3/31m 42s · $0.45

    4. Merge04

      claude-001

      passedpreflight 2/2 · postflight 2/218s

    5. Done

      15m 33s, start to done · 2 models · $1.11

      Escalation route drawn in the workflow; not needed on this ticket.

  3. 03

    Execute the work through SICKR.

    every ticket

    The only step that repeats. This is a real ticket from this product being built, start to finish in fifteen minutes. Open the brief, any state, or the trail — it is the same inspector your team would be looking at.

    Statement of one ticket

    Execution mode dropdown UX needs a fix

    Done · P2 · 14 Sep 2026 · 15m 33s, start to done

    Real run · captured 14 Sep 2026
    State · pick oneCost
    UX Reviewattempt 1passed

    A different provider reviewed the work and approved it. The approval was written back to the pull request, not just recorded here.

    Handled by
    codex-001
    Model
    gpt-5.5
    Started
    15:48:19
    Took
    1m 42s
    Gates
    3 before · 3 after
    4 runs0 failed2 models$1.11 total14m 42s agent time

    Four states, two providers, $1.11. CI was green before a line was written; one model implemented and a different one approved; the approval went back to the pull request; and merge checked that the approval existed before it ran.Not every ticket runs this cleanly. When one does not, the same record shows which gate stopped it and who stepped in.

Bring one workflow. We will run it with you.

That ticket ran on our workflow. Yours runs on the same rails: we set it up with you and run real tickets through it, end to end.

Built by an enterprise systems operator · tested on SICKR’s own product workflow

Apply as a design partner

No. 04 — Why SICKRWhat another agent cannot give you

Humans supervise. AI executes. SICKR runs the team.

Humans supervise

Define what done means, approve what needs approving, and step in when work escalates.

AI executes

The agents you already use, each with a role, inside its permissions, on the record.

SICKR runs the team

Roles, skills, responsibilities, workflows and rules — enforced before, during and after the work.

Use Claude, Codex, Copilot, Cursor, or scripts — SICKR governs the workflow around them.

  • Claude Code
  • Codex
  • Copilot
  • Cursor
  • your own scripts
  • one workflow, governed by SICKR

Intelligence-neutral and tool-neutral: swap the model or the tool, and the roles, rules and record stay.

Intelligence-neutral

Bring any model. Use several at once, and let one check another’s work — the review in the ticket above ran on a different provider from the implementation. Your rules do not change when the models do.

Accountable by construction

Every action attributed, every dollar attached to the work that spent it, every decision on the record. Not a log assembled afterwards: the way the work runs.

We build SICKR with SICKR. The ticket above is not a demo. It is how this product gets built: every change is a ticket that agents plan, implement and review, that a person signs off, and that leaves the record you just read. We run on our own rails before we ask you to.

No. 05 — The askFive teams

Four questions. If two are true, we should talk.

  1. 01

    There is no consistent way your team works with agents.

    Vibe coding, spec-driven, something in between — or you have a process and do not trust it.

  2. 02

    You use more than one model, or want to.

    Picking the right brain for the job, instead of whichever one the tool ships with.

  3. 03

    You cannot say which agent made a change.

    Today it takes human judgement, it is manual, and it is easy to get wrong.

  4. 04

    Policy and control are not negotiable for you.

    You want every detail of how each ticket ran, and no drift from what you approved.

No. 06 — WhoBuilt by an enterprise systems operator

Someone has to stand behind every change.

Arif Manasiya spent 20+ years building enterprise technology platforms across Bloomberg and Amazon: capital markets systems, trading workflows, execution platforms, and mission-critical production infrastructure.

Intelligence alone was never the hard part. Accountability is.

Connect with Arif

Bring one workflow. We will run it with you.

Five teams, eight weeks, and a direct line to the person building it.