Sean O'Connor

72+ AI tools to finish months of work in minutes. 1. Research - ChatGPT - Claude - DeepSeek R1 - Gemini - Abacus - Perplexity Check out threads👇

Got the #LLM semantic to structural matching working. Testing with local #AI #olama . 4b models take 2 mins and not consistent and a little 1B is more accurate and takes 5 seconds! Need to investigate a rag vector filter upstream.

Implementing my own #dos measures for public forms. Honeypots and rate limiting. Any “free” or cheap custom form services will get you price wise if you actually expect any volume on your site.

#AWS apprunner does not play nice with godaddy dns for custom domain validations. Their new two step breaks with underscores in the DNS on godaddy. Forced to use route53.

Finding that small 1B #llm hallucinates less than a 4B for semantic to structural matching. Using #AWS and #bedrock now for my new #saas project.

Using #AWS #kiro to dockerize my apps with specific requirements. It creates scripts, docs, and mult env configs, and deployment YAML. I don’t want to be a docker expert. It’s a breeze.

It energizes me being a #fullstack dev. #react and #ui one minute and #agentic #ai agents in python the next. Throw in C#, serverless cloud services, APIs, infrastructure, and deployment packages. I can build anything.

So many take the easy route because of speed or simplicity. Like #vibecoding push deploy. This leads to vendor lock in and high costs when you scale. Write in a way to make the switch between platforms or services an easier lift. #coding #solopreneur

Using #olama is great to develop local #ai #agents and proof out concepts without needing cloud #llm if your hardware supports it.

Starting a new SaaS project: Patterns: • Natural-language ingestion → structured data • Context tagging + embeddings for signal enrichment • Explainable scoring/rules engine • Personalized weighting with ML evolution • LLM-assisted reflection + feedback loops #ai #AWS

Trying #AWS #kiro for #AI coding some new projects. Using requirements, design, and implementation task documents. Dials in unit test, integration tests, and more.. spec driven development.

Google just released a python library for data extraction! LangExtract is a python library that extracts structured information from unstructured text documents with precise source grounding and interactive visualization. 100% Open Source

The evolution of AI agents in 2025

Asking #AI to help write a job posting for an IT admin, I appreciate it’s incorporation of #devspeak and snarkiness..

Saw a demo of the new #AWS Kiro. This is really a #Cursor killer. Develop #AI agents and docs with #vibecoding . Can’t wait. kiro.dev

@RSBNetwork It’s never him it’s always everyone else

Statement by Donald J. Trump, 45th President of the United States of America

#CloudComputing Notes Cheat sheet #MachineLearning" target="_blank" rel="nofollow noopener">networkwalks.com/cloud-computin… #DataScience #SQL #Cybersecurity #BigData #Analytics #AI #IIoT #Python #RStats #TensorFlow #JavaScript #ReactJS #Serverless #DataScientist #Linux #Programming #Coding #100DaysofCode #NodeJS #golang #NLP #GitHub #IoT #MLOps

Integrating #AWS Athena with our #DotNet web apps to build a bridge to our data lakes.

Working with #AWS CDK to build stacks using #lambda functions from Images. Can't escape the custom #docker images for Lambdas with unique dependencies not out of the box.....

Excited to start building cross platform apps with .Net MAUI now that it's in GA.