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- #TGIM: Unlocking AI's Potential for Mid-Market Efficiency
#TGIM: Unlocking AI's Potential for Mid-Market Efficiency
Welcome, Builders.
Happy Monday. At Able, we’re kicking off 2025 by tackling one of the biggest challenges mid-market CTOs face: where to start with AI. From aligning AI strategies with business goals to managing budget constraints, this month’s newsletter is all about actionable pathways to help you confidently begin your AI journey.
Headlines
Pioneering Leadership
Introducing Michelle Yi: Leading Applied AI Innovation at Able
We’re thrilled to announce that Michelle Yi has joined Able as our new Head of Applied AI in January 2025. With over 15 years of experience spanning roles at IBM and leadership positions in AI innovation, Michelle brings a wealth of expertise and a vision that aligns perfectly with Able’s mission to combine world-class human talent with cutting-edge AI tools.
We’re honored to have her on the team and look forward to achieving incredible milestones together.
A Practical Guide to Integrating AI into Your Workflows

As mid-market companies strategically focus their AI investments on high-impact areas like improving quality control (58%), enhancing customer service (51%), and automating repetitive tasks (45%), the importance of aligning AI initiatives with business goals has never been clearer.
See how we break down the challenges mid-market CTOs face when integrating AI into the Software Development Lifecycle (SDLC). From determining where to start to navigating budget constraints, this article offers actionable steps for leveraging AI-powered tools to accelerate product development, improve quality assurance, and modernize legacy systems. With the right strategy, mid-market companies can unlock efficiencies across the SDLC and confidently drive sustainable innovation.
Leveraging AI for Domain-Specific Success
Domain models are transforming the way businesses leverage AI by offering industry-specific expertise right out of the box. Unlike generic models, domain models are purpose-built, trained on curated data relevant to particular industries or functions. This specialization enables faster deployment, reduced costs, and improved accuracy for domain-specific tasks.
By using domain models as a foundation, development teams can accelerate time-to-value, optimize resources, and achieve superior performance with minimal fine-tuning. For mid-market organizations, these models offer a practical and cost-effective way to unlock AI’s potential while maintaining control over proprietary data.
AI Pulse
What’s Trending in AI
🔍 This Week in AI:
DeepSeek R1, Explained Simply 🧠 Want a breakdown of the DeepSeek R1 paper? This video covers chain-of-thought reasoning, reinforcement learning, and model distillation. Watch here: YouTube
Meta’s AI War Rooms? Mark Zuckerberg is assembling specialized teams to accelerate Meta’s LLaMA advancements, while China’s DeepSeek AI is making major moves. Read more: Fortune
💡 Inside Able:
Our Head of Applied AI is excited about a super cool paper from Sakana.ai on self-adaptive LLMs that update their weights live—potentially eliminating the need for LoRA fine-tuning.
📄 Paper: arXiv | 💻 Code: GitHubAI is evolving fast, and Head of Applied AI, Michelle Yi, highlights two key trends reshaping how mid-market companies should approach it: efficiency over data and AI bridging the real world through advanced models. 🚀 Watch the snippet here: YouTube.
Let’s Build Together
Able is a product engineering company. We empower our world class talent with leading edge AI tools to build you the right software, fast. Our efficient and proprietary processes increases capacity for our partners and delivers bottomline results. We are a team of 60+ software development experts – Strategists, Designers, Engineers and Project Managers – distributed throughout North and South America.
If you’re interested in working with us, contact us here.