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Is your documentation holding back your product?
Most developers ship great products and then write a 5-line README that confuses everyone.
I'm Kelechi a Technical Writer and Cybersecurity Analyst. I turn messy, incomplete docs into clean professional references developers actually read.
What I deliver:
REST API Documentation
SDK & Library Guides
GitHub READMEs
User Guides & SOPs
First project? I'll write a FREE sample before you pay anything.
DM me let's talk!
The network for creativity
Join 1.25M professional creatives like you
Connect with clients, get discovered, and run your business 100% commission-free
Creatives on Contra have earned over $150M and we are just getting started
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Dan Holdsworth and Luke Allen ship brands as a code ready repo.
The handoff includes global CSS, a clip JSON file, an agent file, and a human-readable README. Clients drag and drop it into their codebase and the brand is operable from day one.
They started doing this because clients kept improvising after handoff. A PDF gets opened once and forgotten. A repo stays in the codebase as a source of truth.
The thinking matters. The handoff is the start of the brand's life in production. If the system breaks the first time someone extends it, the design work didn't finish.
They also talked about taking only two projects at a time, catching a logo that sat too close to a Pinterest reference and redoing it the same day, and the difference between cheap and affordable when you raise prices.
Full episode: https://www.youtube.com/watch?v=Gl0Q2Xjw1Ao
AI is an analytical tool it doesn't have tast or creative intelligence or emotional intelligence it will never be better than humans in that because it has no emotions or creativity
What if anyone on your team could ask your data a question and get a live dashboard back in under a minute?
That was the brief. Business users were locked out of their own data. Every question waited on someone who could write SQL, data sat across disconnected systems, and security teams refused to send sensitive records to third-party AI tools.
So we flipped the model. Instead of moving enterprise data to an AI product, we moved the AI analytics product into the customer's AWS account.
What we built:
• Natural-language querying that turns plain-English questions into governed dashboards in under 60 seconds
• Federated queries across SQL and NoSQL sources through Trino
• AI query generation on AWS Bedrock Agents, with Bedrock Guardrails keeping model output in bounds
• Dashboards generated with Apache Superset, plus proactive anomaly and trend alerts
• A white-label React widget that embeds in any product
• Role-based access, row-level security and enterprise SSO enforced at every layer
The result:
Zero data egress. The whole platform deploys inside the customer's VPC and is live on AWS Marketplace.
Building AI features for a data-heavy or regulated product? Let's talk about doing it without your data leaving your cloud.
Renewable energy production changes constantly, and grid operators need faster ways to understand what is happening across load, generation, storage, and market conditions.
Gridora explores a SaaS dashboard experience built for energy forecasting and balancing.
The dashboard surfaces forecasted peak load, curtailment risk, available storage, spot market price, generation sources, and recommended next actions in one clear workspace.
Natural imagery, soft neutral surfaces, and green accents connect the interface to the renewable energy context while keeping the product practical and easy to scan.
