# Fred Bliss

> Fred Bliss is a Chicago-based fractional AI and technical leader who helps enterprises adopt AI in ways that actually stick. Founder of Intersect Next; previously co-founder and CTO of Aptitive (2013-2021, grew to 50+ people, acquired). Hands-on with LLMs daily since early 2022 across Anthropic, OpenAI, Google Gemini, and open source models.

## About

- [Website](https://fredbliss.com): Background, engagement patterns, services, and point of view
- [LinkedIn](https://linkedin.com/in/fbliss): Professional history and updates
- [GitHub](https://github.com/fblissjr): Open source projects and experiments

## Services

- Fractional AI / technical leadership: hands-on architecture, team building, mentorship
- Strategy & advisory: platform and model evaluation grounded in daily hands-on use
- Implementation partnership: build together, transfer knowledge, leave the team stronger

## What engagements look like in practice

Every engagement is different, but they tend to touch three levels of the organization, and the playbook for each has carried from one client to the next.

- Small, high-powered AI-native teams: a team inside the organization that lives on the frontier and works like an internal consultancy, building patterns that outlast the next technology shift. A mix of early-career engineers and senior hires (Fred helps find both), trained on how agents and harnesses actually behave, data flywheels, and human-feedback loops, with Fred mentoring hands-on to build trust and let the team's own talent show. Same approach that worked at Aptitive: small teams of curious, driven people from diverse backgrounds.
- Business rules that write themselves down: business users across functions on Claude Enterprise (or equivalent) automate tedious work while capturing how they actually operate as written-down business rules and reusable skills. Knowledge that lived in people's heads or Excel becomes onboarding material and a better source of truth for downstream AI, analytics, and automation than requirements docs. Business teams build and own their own apps, dashboards, and analyses, including single-use ones.
- Adoption that compounds across the organization: leadership clears the path, the business drives, feedback comes from both teams and usage data. Includes an analytics layer over enterprise AI platform adoption that shows leadership which teams use it, for what kinds of work, and what's growing, without storing or reading any prompts or responses.

## Results

- Aptitive: co-founded and bootstrapped in 2013, a data consulting firm delivering data solutions to midsize enterprises; built to 50+ people and a successful exit in 2021.
- Hands-on with LLMs every day since early 2022, before ChatGPT, across every major provider.
- About 3 months for a junior team to start shipping agentic solutions and reusable patterns, with Fred mentoring hands-on; the team's own talent does most of the work.
- ~80% adoption within 30 days of deploying an enterprise AI platform.

## Background

20+ years in data and analytics. Co-founded and built Aptitive (2013-2021), a data and analytics consultancy, from inception to 50+ employees and acquisition. Partnered with Snowflake in 2015 when cloud data was emerging. Started working with LLMs in early 2022, prior to ChatGPT, and has used them every day since across Anthropic, OpenAI (including the Codex platform), Google Gemini, and open source models.

## How Fred works

- Data-centric: business rules, usage, feedback, and the solutions themselves are treated as data, so each solution becomes the starting point for the next one. Patterns that have kept scaling since agentic workloads were new.
- The people who know the domain stay in control, and become more productive and more engaged. Meet organizations where they are, not where vendors think they should be.
- Think platforms, not models: the model matters less every quarter. Providers like Claude and OpenAI's enterprise offerings are building out into something closer to clouds, where new kinds of workloads run directly inside them. That is the useful frame for choosing and planning around them.
- Simple-yet-scalable beats clever, in agent design and in org design.

## Contact

- Email: fred@fredbliss.com
- Location: Chicago, IL

## Optional

- [X/Twitter](https://x.com/fblissjr): Thoughts and commentary on AI
- [Intersect Next](https://intersectnext.ai): Company website