KUJO — Trust at the speed of AI.
18-slide investor briefing with source evidence, recorded execution and editable planning assumptions.
1. Trust at the speed of AI.
The programming language and accountability infrastructure for agent-driven development.
Investor briefing / November 2026
2. Software production is outpacing verification.
Agents can report completion. Teams still need a reviewable chain from requested work to release decision.
- 01
The claim
“Tests passed. Ready to merge.” An illustrative agent statement.
- 02
The evidence
Command, exit code, changed revision, environment and retained failure output.
- 03
The gap
Useful logs already exist. Connecting them across tools and review boundaries remains work.
02 / The accountability problem
Thesis · existing agent controls acknowledged
3. Greater autonomy requires stronger accountability.
The cost of an unverified action grows as agents gain authority.
- 01
Suggest code
Human selects the change → diff review
- 02
Complete a task
Agent edits and runs commands → execution records
- 03
Operate a workflow
Retries and external effects → boundaries, recovery and approval
03 / Structural shift
Conceptual progression; not a measured adoption curve
4. AI use is broad. Trust remains conditional.
Adoption of AI assistance is not evidence of autonomous production deployment.
- use coding assistants or coding agents at work
- 65.9%
- use AI agents or automated workflows at work
- 26.2%
- trust AI when answers are easy to validate
- 48%
04 / Why now
M03–M04 · Stack Overflow Developer Survey 2026
5. Build with clarity. Operate with control.
The language is the long-term foundation. Existing tools offer an earlier route into engineering workflows.
- 01
Clarity
Kujo language / Spec / Eval: explicit intent and testable outcomes.
- 02
Context
MCP / CaseFile / RunLedger: useful inputs, debugging evidence and run records.
- 03
Control
Dispatch / Workcell / ShipCheck: orchestration, bounded execution and release checks.
05 / The Kujo system
T01–T14 · tool boundaries remain distinct
6. Accountability spans the whole task.
Each component owns a specific responsibility. A reviewable workflow composes their artifacts explicitly.
- 01
Instruction → Context
Spec / PackWrite → MCP and repository context
- 02
Execution → Evaluation
Dispatch / Workcell → Eval result artifacts
- 03
Evidence → Review → Release
CaseFile / RunLedger → reviewer → ShipCheck gate
06 / Lifecycle
Composition map; not automatic end-to-end enforcement
7. The foundation is already being built.
Inspect the implementation and its limits, then reproduce the smallest useful proof.
- 01
Language and VM
Kujo 1.9.0 is documented; a local 1.9.0 binary executes the recorded fixture tooling.
- 02
Bounded execution
Workcell 1.3 documents Docker/Podman limits, explicit exports and receipt verification.
- 03
Reviewable artifact
This presentation uses the native Kujo builder. Its demo retains a failing command, correction and evaluation.
07 / Engineering proof
T01, T03, T08, T14 · release documentation ≠ all HEAD features
8. A claim becomes inspectable evidence.
Recorded local coding fixture: correct a post-money ownership calculation. Inspect what failed, what changed and what passed.
- 01
Request
Return 20% for $6M raised at $30M post-money.
- 02
Execution
CaseFile captures real Node assertion failure and corrected execution.
- 03
Decision
Eval checks the correction. Accept this fixture; no production release.
08 / Recorded demonstration
Assistant-authored seeded fixture · CaseFile + Eval · local host
9. Adopt the ecosystem before the language.
Keep application code in its existing language. Introduce accountability at the workflow boundary.
- 01
Today: wrap the task
Use CaseFile for command evidence and Eval for explicit repository checks.
- 02
Then: control execution
Adopt Dispatch or Workcell after validating the target environment and runtime pins.
- 03
Over time: go deeper
Choose Kujo for new agent tooling where native language integration adds value.
09 / Adoption without migration
T02–T04, T08 · tools have their own runtime dependencies
10. Start with teams already delegating engineering work.
Proposed beachhead: agent-platform builders shipping repeatable engineering workflows.
- 01
Buyer / user
Platform engineering lead / engineers operating coding-agent harnesses.
- 02
Immediate pain
Failed runs are expensive to reconstruct. Review spans commits, logs and agent transcripts.
- 03
Purchase hypothesis
Pay for retained evidence, controlled execution and team review if they reduce investigation time.
10 / Initial customer
Proposed segment; no customer interviews or demand validation
11. Open tooling can lead to a commercial operating layer.
Earn developer trust through useful local tools. Charge for shared operational responsibilities.
- 01
Available foundation
Open repositories and local developer tooling.
- 02
Proposed team service
Hosted evidence, retention, shared review and execution capacity.
- 03
Proposed enterprise tier
Organization policy, deployment controls, support and governance.
11 / Business model
Hosted offerings and pricing are proposals, not available SKUs
12. A focused entry market can support a meaningful business.
Illustrative bottom-up model. Organization counts and annual contracts are assumptions to validate.
- initial target organizations × $24K ACV
- 2,000
- illustrative annual serviceable revenue pool
- $48M
- 100 customers × $24K; milestone scenario, not forecast
- $2.4M
12 / Market model
Planning only · editable assumptions in appendix
13. Accountability requires more than generating code.
Existing platforms are strong. Kujo must win on useful evidence and the cost of operating reliable workflows.
- 01
Coding agents / GitHub
Generation, repository context and review are already integrated into major developer surfaces.
- 02
Orchestration / LangGraph
Persistence, recovery and human review are established capabilities.
- 03
Kujo opportunity
Connect explicit contracts, bounded work and inspectable artifacts. Prove adoption before claiming a moat.
13 / Position and defensibility
C01–C02, T01–T14 · no exclusivity or benchmark superiority
14. Meet developers inside their existing workflows.
The planned December 2026 open-source campaign should produce repeat usage and customer learning.
- 01
Discovery
GitHub releases, technical demos, docs and reproducible fixtures → qualified visits.
- 02
Activation
Agent harness recipes and MCP tooling → first successful evidence run.
- 03
Retention → revenue
Repeat weekly runs → design-partner discussions → paid pilots and renewal evidence.
14 / Distribution
Campaign and partnerships planned; measure cohorts, not raw impressions
15. Execution is visible. Demand still needs proof.
Engineering output, external adoption and commercial traction are different measures.
- 01
Engineering output
Public repositories, documented releases and the locally reproduced evidence fixture.
- 02
External adoption
Verified outside usage, retention and independent integrations: data not supplied.
- 03
Commercial traction
Design partners, paying customers and revenue: data not supplied. Complete before investor distribution.
15 / Momentum
Unavailable is not zero; no invented traction
16. Built through sustained open-source engineering.
Robert DeVore connects open-web product work with a growing language and developer-tooling ecosystem.
- 01
Background
Public biography describes years of WordPress, WooCommerce, plugins and publishing systems.
- 02
Current work
Language/runtime infrastructure, orchestration, evaluation, telemetry and evidence workflows.
- 03
Team enabled by capital
Proposed hires in runtime, execution reliability and developer experience; later customer engineering.
16 / Founder and team
F01 · first-person source; no invented tenure, team or security credentials
17. Capital turns a technical foundation into an adopted platform.
Working seed scenario. Financing terms and hiring pace remain assumptions.
- target raise
- $6M
- post-money valuation or SAFE cap assumption
- $30M
- planned runway, including reserve
- 24 mo
17 / Investment and milestones
20% simplified ownership before further dilution · $150K founder annual base
18. Agents will build more software.
The organizations deploying it will still be accountable for what it does.
18 / The vision
KUJO · Trust at the speed of AI.