No-Code Agentist

⇨ Key features: • No-code agent builder • Approved context & tools • Usage visibility • Cost & budget governance • Reusable AI workflows

Don't read this article. Give it to your agent. It's the 10-point checklist an AI agent needs to make viral content: eyes, hands, a research feed, a memory. Paste it into Claude, ChatGPT or Codex. It'll tell you what's missing and how to fix it 👇 https://t.co/eq8Li1JOoi

How to complete a 5-day AI agent sprint... Btw, if you need help running these, we, at @tenex_labs, do free 5-day agent sprints for enterprises (link at the bottom). 1) Build the map (of opportunities) Length: 60 minute meeting Description: Uncover the biggest problem areas in the business where agents could help, and understand the business's core systems and data Key details: - Finding every use case, re-imagining the work and building champions - Output: Target list of 30-to-60 use cases; Size the opportunity around 10-to-20 of them; Design 3-4 agents; Identify one champion per function Where to look: - Cost structure: rank teams by headcount and spend. The biggest teams usually hide the biggest agents. - Org chart: for every team over about 5 people, ask what comes in and what goes out. - Follow the work: trace one invoice, hire or ticket across every team that touches it. - Queues and recurring work: shared inboxes, ticket and approval queues, weekly reports and standing meetings. - Surveys and old AI intake lists, if your org has them. 2) Complete the map (audit speedrun) Length: 2 days Description: Build a strong ROI case for each opportunity and prioritize by the biggest opportunities that can be delivered soonest The business case: - Labor: annual hours × % of time removed × loaded hourly cost. Call it capacity returned, not cash, and say how it becomes cash: fewer hires, less contractor or BPO spend, or people moved to revenue work. - Financial: faster collection (amount collected sooner × cost of capital), less bad debt, recovered revenue, lower spend, avoided BPO cost and captured discounts. - Quality and risk: volume × error rate × cost per error × % prevented. Usually the softest number, so never let it carry a case alone. 3) Connect to your systems Length: All public MCP, OpenAPI, and GraphQL systems set up instantly, custom or private connectors mocked out for the sprint Description: Use a gateway product to wire up all key systems, building custom connectors or MCP servers if necessary Key details: give the agent a map of your data & organization - Data map: The tables or objects that matter, what each holds, key fields, join paths, standard filters and field meanings in plain words - Query recipes: Tested queries or API calls for the agent's common questions - Ignore list: What looks relevant but isn't, and why - Organization map: Business units, clients, retailers, accounts, company codes and cost centers, and how they relate - Aliases: How people name things, mapped to system IDs - Glossary: Your company's terms and acronyms - Gotchas: Known traps 4) Define the agent behavior Length: 1 day Description: Write out the agent's core behavior and build up its set of capabilities as skills with a skill router as the entrypoint Order of operations: - Pin the outcome the agent owns. - Map today's process: trigger, steps, people, systems, decisions, approvals, exceptions, volume and time. - Re-imagine it from first principles. - Brainstorm 10 to 20 capabilities. - Shape behavior: router, skills, constitution, autonomy levels. - Map connections and listeners. - Draft the context blueprint. - Size the business case with the Business Case Method (above). - Script the golden demo. - Review with the workflow owner. 5) Prototype and test agent internally Length: 1 day Description: Run the agent's core workflows in Slack or Teams, upgrading the agent to a custom web app if necessary Principles: - Write the golden demo before writing code. The script decides what to build and what data to seed. - Emulate, don't integrate. No production systems or live credentials. - Real on the surface, synthetic underneath. Their names, templates and terms, with our data. - Same path as production. Agents call emulators through data gateway, so going live means swapping the connection, not rebuilding. - Demo path first. Get the golden demo running end to end before adding anything else. 6) Present to key stakeholder Length: 1 hour Description: Run through an initial demo with our internal champion and transcribe all feedback 7) Iterate on the agent Length: 1 day Description: Make key changes and polish the agent's behavior until it can consistently nail the "golden demo" 8) Demo day Length: 1 hour Description: Present the agents we've prototyped and their business cases to executive stakeholders and define the longer term roadmap Key details: Presenting prototyped agent + the long-term production case for the use case Must haves for a demo: - Follows one protagonist for 5 to 8 minutes - Starts with the agent reacting to an event, email or schedule, not a prompt - Handles a messy case - Works in a real artifact and shows it - Shows an approval enforced through data gateway - Finishes the loop: send, log, follow up - Uses next-step suggestions and the client's own language - Ends on a business number tied to the business case P.S. if you want a free 5-day AI agent sprint for your business (that finishes with up to 4 working prototypes), we do this for select enterprises at @tenex_labs. Fill out the form here: https://t.co/qi43VCnNQ0