Operating memory
Sources, decisions, examples, and learnings ready to be reused.
We install criterio: operational judgment agents can follow.
You do not need more AI. You need to redesign how you use it.
We organize information, decisions, processes, and judgment so people and agents work better with AI.
You work directly with Darío and Camilo. No sales theater. No demo theater.
What remains after BC leaves
The deliverable is not a demo. It is capability that keeps working.
If all that remains is a presentation, we failed. The work should remain as memory, workflows, evals, permissions, and owners the company can operate.
Explicit judgment
Standards for good work that humans and agents can apply and evaluate.
Work harness
Permissions, tools, traces, evals, limits, and recovery around the model.
Human owner
A person responsible for verification, exception approval, and system improvement.
Legible company
If the work cannot be read, it cannot be automated well.
BC turns scattered files, decisions, examples, rules, and owners into operating context for humans and agents. This is not document cleanup. It is infrastructure for AI-enabled work.
How we work
Real work→trace→judgment→eval→agent→memory
Starting point
What do you want to move with AI now?
Shared language
Align judgment
I want my team to understand where to use AI, what risks to watch, and where to start.
Duration: 60 to 90 minutes.
Engagement model: Executive session scoped by audience and required depth.
Default wedge
Explore a challenge with AI
I have a concrete challenge and want to explore an AI solution without losing control.
Duration: 2 to 4 weeks.
Engagement model: Bounded sprint; scope defined during the start brief.
Operating layer
Elevate the organization with AI
I want my organization to work better with AI: organized information, workflows, agents, permissions, and owners.
Duration: 3 to 6 months.
Engagement model: Phased program scoped by workflows, data, and governance.
Proof patterns
We do not leave demos. We leave operating capability.
Cases are framed as patterns: what happened before, what BC installed, and what kept working under human ownership.
Marketing Agent Model
Replacing fragmented marketing agency work with a governed agent-assisted operating model.
- Before
- The work was not a single missing prompt. It was a missing operating model for briefs, sources, judgment, review, and execution.
- Installed
- Agent-assisted workflow for briefs, assets, and campaign decisions.
- What kept working
- The team could reuse context instead of restarting from scattered notes.
Pricing Intelligence
Turning competitor pricing research into a repeatable, evidence-backed monitoring workflow.
- Before
- Pricing evidence lived across websites, files, and internal memory. The process was too fragile to repeat with confidence.
- Installed
- Repeatable research workflow for competitor pricing evidence.
- What kept working
- Research became easier to repeat and audit.
Technical Knowledge Agent
Turning expert technical knowledge into a personal and commercial support agent with curated sources.
- Before
- The knowledge existed, but it was not packaged as reusable memory with source boundaries, confidence, and escalation.
- Installed
- Curated source base for technical answers.
- What kept working
- The expert became more scalable without losing ownership.
Financial Operating Agent
Moving from fragile spreadsheets and intuition to agents that help quote, compare suppliers, and understand cash/margin by project.
- Before
- Spreadsheets and intuition were doing too much work. The company needed reusable financial context and decision support.
- Installed
- Agent-readable quoting and supplier comparison workflow.
- What kept working
- Quotes became easier to compare and explain.
Board Agent
Helping leadership teams query board-level context, decisions, and follow-ups through a governed agent.
- Before
- Board knowledge was valuable but scattered across decks, notes, decisions, and institutional memory.
- Installed
- Governed context layer for board materials.
- What kept working
- Leadership could retrieve context without depending on memory alone.
Frameworks
The language behind the work
Digital Brain
A Digital Brain is company memory that agents can reuse without hiding the source of judgment.
Read frameworkJurisdiction Map
A workflow is not ready for agents until someone can verify, sign, and audit the result.
Read frameworkAgent Control Plane
Agents need memory, permissions, evals, owners, traces, approvals, runtime, and recovery.
Read frameworkCyborg Ladder
AI maturity moves from casual use to reusable capability when people become operators and system designers.
Read frameworkWho Business Cyborgs Is
Two operators. One shared thesis: install criterio.
Business Cyborgs combines commercial speed, business judgment, and installed technical capability. Darío Palacio and Camilo Serna work from Colombia to turn AI pressure into systems humans can operate with leverage.
Medellín, Colombia
Darío Palacio Isaza
Business Cyborg.
Atomika / 10AMPRO.
He operates from the idea of “small particle, massive energy”: an AI-augmented solopreneur can create the impact of a full team. His edge is speed: finding high-value quick wins and turning technology into measurable outcomes.
25+ years across digital and technology ecosystems: e-commerce, startup accelerators, UX/UI agencies, custom software shops, product management, digital marketing, and Lean Startup methodology.
Native Spanish, English, and functional Portuguese.
- /Looks at business work through one constant question: “Could this be done with AI?”.
- /Understands technology well enough to direct implementation without selling technology for its own sake.
- /Reads Latin American markets and cultural dynamics with unusual practical context.
Bogotá, Colombia
Camilo Serna Zamora
Business Cyborg.
Kohete.
He works from the thesis that AI is not bought as a tool; it is installed as capability. His focus is turning real work into reusable systems: digital brains, agents, workflows, operating memory, and installed criterio.
15+ years turning ideas into businesses, products, and organizations under high uncertainty, with experience in innovation, new ventures, product management, business model design, digital strategy, and AI implementation.
Native Spanish and functional/professional English.
- /Connects business judgment with installed technical capability.
- /Designs systems that turn scattered work into operable workflows, memory, and agents.
- /Combines business, product, technology, narrative, and organizational adoption to move opportunities into fast execution.
Resource
Playbook: how to know if a workflow is ready for agents
A short guide for evaluating owner, sources, permissions, evals, and next step before building. The playbook will be available soon. For now, book a conversation and we will review your workflow with you.
For agents and crawlers
Make BC easy to classify.
A buyer's agent should understand fit, inputs, outputs, engagement model, constraints, and the next step without guessing.
Start brief
Bring one workflow. Leave with the right next move.
AI solved part of execution. The question is direction.