Who is Anthony Washington Sr.?

Anthony Washington Sr. is a U.S. Army and Maryland Army National Guard veteran, a coach and official of more than twenty years, and the founder of After Today, LLC. He builds leadership training, athletic recruiting education, and people-first AI systems for student-athletes, families, schools, and organizations. He is based in Pennsylvania and works primarily across Pennsylvania and Maryland.

What does Anthony Washington Sr. do?

He works in three connected areas: athletic recruiting education that gives student-athletes and families a repeatable daily process, leadership training for first-time supervisors and public-sector leaders, and people-first AI and workflow implementation for organizations. He also speaks and runs workshops for schools, teams, and districts.

What is athletic recruiting infrastructure?

Athletic recruiting infrastructure is the repeatable system a family or program uses to manage recruiting — film, academics, communication with coaches, eligibility tracking, and follow-up — instead of relying on exposure events and luck. Anthony teaches recruiting as infrastructure so progress comes from a daily practice rather than a seasonal scramble.

What does people-first AI implementation mean?

People-first AI implementation means adopting AI to improve the work without displacing or sidelining the people who do it. In practice that means starting from the actual workflow, keeping a human accountable for decisions, training staff on the tools they will use, and setting guardrails before scale — not buying software and hoping the team adapts.

Who are Anthony's programs designed for?

Student-athletes and their parents, high school and grassroots coaches, athletic programs, schools and districts, first-time supervisors, public-sector leaders, and organizations that want leadership training or help implementing AI without leaving employees behind.

Does Anthony Washington Sr. provide leadership training?

Yes. He trains first-time supervisors and team leads on the first ninety days, difficult conversations, accountability, and building trust, drawing on his military service, public-sector supervision, and coaching experience. Training is delivered as courses, workshops, and organizational consulting.

How can a school, district, or organization work with Anthony?

Schools, districts, and organizations can book speaking engagements and workshops, bring in leadership training for supervisors and staff, or engage him on recruiting support and AI and workflow implementation. Start on the contact page and say which of those you need.

How can I book Anthony Washington Sr. to speak?

Send an inquiry through the contact page with your event date, audience, format, and location. The speaking page lists topics, session formats, and the audiences he speaks to most often.

Where is Anthony Washington Sr. based?

He is based in Pennsylvania and works primarily across Pennsylvania and Maryland, with virtual sessions available beyond that area.

What is an LLM, and why does it matter which one I use?

An LLM (large language model) is the AI engine inside tools like ChatGPT or Google Gemini that generates text. Which one you use matters because different models have different accuracy, speed, cost, and access policies; the right choice depends on your specific leadership task.

Is ChatGPT the only AI tool I should learn?

No. ChatGPT is powerful and widely used, but Google Gemini, Anthropic Claude, and others offer different strengths. Learning the core skill of how to write clear prompts and fact-check AI output matters more than mastering one tool.

Does it cost money to use AI models?

Not always. Many models offer free tiers with limits on usage; others charge per query or require a subscription. Free tools are often sufficient for drafting emails, summarizing documents, and planning work; paid versions are faster and have fewer restrictions.

If I choose one AI tool now, am I locked in forever?

Not forever, but switching tools carries a cost in time and relearning. If you build all your workflows around one platform and that company changes pricing or access, you may need to adapt; learning the underlying skill (clear prompting and critical thinking) reduces that risk.

Why do AI companies keep releasing new models?

Competition for market share and revenue. Each new model claims to be faster, more accurate, or cheaper; companies race to claim performance advantages and lock in users and paying customers.

How do I know if a new model is actually better than the one I am using?

Independent benchmarks and user reports help, but most companies control how their models are tested. Your best evidence is trying the tool on your real work; if a new model helps you draft delegations or summarize policy faster, it is better for you, regardless of marketing claims.

What should I do right now about the LLM battle?

Pick one or two tools and learn them well. Focus on the skill (writing clear prompts, fact-checking results, integrating AI into your workflow) rather than the tool itself; the skill transfers when the market shifts.

Home › Blog › The LLM Battle You Did Not Know About (And Why It Matters for Your Leadership)

The LLM Battle You Did Not Know About (And Why It Matters for Your Leadership)

ai · August 24, 2026

Different AI companies are racing to build better language models. Understanding this competition helps you pick the right tool for your leadership work.

Key takeaways

Multiple AI companies (OpenAI, Google, Anthropic, Meta, others) are competing to build better large language models; this competition is reshaping the AI tools available to you.
Each model has different strengths, costs, and access patterns; the "best" model for drafting a delegation email may not be the best for summarizing a policy document.
Model performance is not fixed; companies release new versions regularly, and what was expensive or limited last month may be cheaper or more capable this month.
Choosing one platform (like ChatGPT or Google Gemini) carries a hidden cost: you become dependent on that company's pricing, access policies, and product roadmap.
A practical leadership approach is to learn the core skill (clear thinking, fact-checking, prompt structure) rather than mastering one tool, so you can adapt as the market shifts.
The competition is real, but it is not transparent to you; companies do not publish detailed comparisons, so your choices are often based on marketing claims rather than independent evidence.
For everyday leadership work, "good enough" models are cheaper and faster; the bleeding-edge competition matters more if you need specialized performance (like coding or structured data analysis).

You hear about a new AI model every few weeks. ChatGPT, then GPT-4, then Google Gemini, then Claude, then something else. If you are a leader trying to adopt AI tools practically and responsibly, this noise feels overwhelming. But underneath the announcements is a real competition with real consequences for how you work and what you can and cannot do.

Understanding this competition is not about becoming a technology expert. It is about knowing why your choices matter and how to make them without getting lost in marketing claims.

What Is Actually Happening

Multiple AI companies are building large language models, or LLMs. These are the AI systems that power chatbots and text-generation tools. OpenAI (ChatGPT), Google (Gemini), Anthropic (Claude), Meta (Llama), and others are all competing to build models that are faster, more accurate, cheaper, and more capable.

This is a real race with real money and real stakes. Training a state-of-the-art model costs tens of millions of dollars. Companies recoup that investment by charging for access, selling enterprise licenses, or licensing models to other platforms. The first company to release a model that performs well enough at a low enough cost wins users and market share.

Here is what you see: new model releases every few months, each one claiming to be better. Here is what is actually happening: companies are competing for the right to be your default AI tool.

Why This Competition Affects Your Leadership Work

When you pick one AI tool and learn it, you are making a bet. You are betting that the company keeps it reliable, keeps it affordable, and does not change the terms in ways that hurt your workflow. Sometimes that bet pays off. Sometimes it does not.

Consider a concrete example: you choose ChatGPT as your tool for drafting delegation messages to your team. You get good at writing prompts; you build ChatGPT into your weekly routine. Then OpenAI changes the pricing or access policy. Or Google releases a model that is dramatically cheaper and faster. Or Claude gets better at understanding the nuance in a difficult conversation you are planning. Now what? You can switch, but switching costs time.

This is not hypothetical. Pricing and capability shift constantly. A model that was expensive last year is cheap this year. A model that could not do structured analysis last quarter can now. Companies add and remove features without warning.

The Hidden Cost of Picking One Tool

When you become dependent on one model or one platform, you become dependent on the company's decisions. They control when you get new features, how much you pay, whether your data is used for training, and what happens if they decide to shut down or pivot. You do not get a vote.

The companies also do not publish transparent comparisons. You cannot easily run your delegation email through Claude, ChatGPT, and Gemini side by side and measure which one performed better. So your choice is based on trial and error, word of mouth, or marketing claims.

This is why learning the core skill matters more than mastering the tool. When you understand how to write a clear prompt, how to fact-check the output, and how to integrate AI into your leadership workflow, you can switch models without losing your competence. The skill transfers; the tool does not.

What This Means for You Right Now

You do not need to chase every new model. Pick one or two tools that are available, affordable, and accessible to you. ChatGPT, Google Gemini, and Claude all have free or low-cost tiers. Anthropic and others offer open-source models if you want to avoid licensing altogether.

Use the tool for real work: drafting emails, summarizing policy, planning a project, preparing for a difficult conversation. Learn what it does well and what it does not. Notice when a newer model claims to solve a problem you have. Try it. If it genuinely helps, switch.

The competition between these companies is real and ongoing. But it also means you have choices, and those choices are getting cheaper and more capable. Your job is not to predict the future of AI. Your job is to learn the skill that works with any of these tools, then adapt when the tools change.

For more on how to integrate AI into your leadership work responsibly, see AI for Leaders: Save Time Without Losing the Human Touch. If you are ready to build AI into your systems and workflows, 52 Weeks walks you through a structured 52-week growth journey that includes practical AI adoption.

Frequently asked questions

What is an LLM, and why does it matter which one I use?: An LLM (large language model) is the AI engine inside tools like ChatGPT or Google Gemini that generates text. Which one you use matters because different models have different accuracy, speed, cost, and access policies; the right choice depends on your specific leadership task.
Is ChatGPT the only AI tool I should learn?: No. ChatGPT is powerful and widely used, but Google Gemini, Anthropic Claude, and others offer different strengths. Learning the core skill of how to write clear prompts and fact-check AI output matters more than mastering one tool.
Does it cost money to use AI models?: Not always. Many models offer free tiers with limits on usage; others charge per query or require a subscription. Free tools are often sufficient for drafting emails, summarizing documents, and planning work; paid versions are faster and have fewer restrictions.
If I choose one AI tool now, am I locked in forever?: Not forever, but switching tools carries a cost in time and relearning. If you build all your workflows around one platform and that company changes pricing or access, you may need to adapt; learning the underlying skill (clear prompting and critical thinking) reduces that risk.
Why do AI companies keep releasing new models?: Competition for market share and revenue. Each new model claims to be faster, more accurate, or cheaper; companies race to claim performance advantages and lock in users and paying customers.
How do I know if a new model is actually better than the one I am using?: Independent benchmarks and user reports help, but most companies control how their models are tested. Your best evidence is trying the tool on your real work; if a new model helps you draft delegations or summarize policy faster, it is better for you, regardless of marketing claims.
What should I do right now about the LLM battle?: Pick one or two tools and learn them well. Focus on the skill (writing clear prompts, fact-checking results, integrating AI into your workflow) rather than the tool itself; the skill transfers when the market shifts.

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