Richard Best is a design professional who writes about how AI is changing design tools, workflows, and careers. In one LinkedIn post, Best also invited applicants to join a design team at Game7.
Richard Best is most useful for pointed commentary on AI-driven design tool and career shifts.
Best for
A design tooling brand wanting a moderated talk or advisory session on AI workflows.
Not for
A vendor seeking high-volume demo signups, guaranteed design-buyer reach, or upbeat product endorsement.
Key takeaways
AI adoption is a career-risk issue, not just a tool preference.
Design roles may split into hybrid, AI-led jobs.
Judge a design tool by concrete roadmap and costs, not brand.
Check first: Confirm audience demographics, engagement rates, and whether they accept paid collaborations or advisory work.
Main ideas
AI adoption is a career-risk issue, not just a tool preference · Design roles will split into hybrid, AI-led jobs · Judge a design tool by its concrete roadmap and costs, not its brand
Richard Best writes about how AI is changing design careers and tools.
The posts forecast how design roles may shift, criticize specific gaps in Figma’s AI and design-system workflows, and describe a design-team hiring effort at Game7 in blockchain gaming.
The posts show these as parts of Best’s public work, but do not establish whether a book, show, business, or earlier work is also central to why people search the name.
The posts do not establish that broader identity context.
Best connects broad predictions about AI and design work to concrete examples.
In one post, they map possible changes across product design, UX research, visual design, and content creation; in another, they support criticism of Figma with named workflow issues, costs, and competing tools.
The contrast is useful: the first is a forward-looking forecast, while the second is a detailed product critique, not neutral product research.
A separate Game7 hiring post shows a practitioner and team-leadership context, but is an announcement rather than an argument.
Read them for pointed commentary on design tools and possible career shifts; treat the forecasts as their views, and consult the linked longer articles for more detail.
Richard Best writes about how AI is changing design work from two angles: the tools designers use and the roles they hold.
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Their recurring argument is that AI is compressing the distance between idea and shipped product, leaving designers and teams exposed when their tools slow them down.
They pair that warning with a role-by-role forecast of hybrid jobs and a detailed critique of Figma, arguing that tool choice has career consequences.
A separate hiring post shows a working priority: building a design team for blockchain gaming.
AI adoption is a career-risk issue, not just a tool preference
Richard Best argues that when AI collapses concept-to-shipped timelines, being slowed down by a primary design tool is not a minor inconvenience.
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If your tools cannot match the industry's accelerating pace, you cannot match it either, and you risk being replaced by the technology your tools failed to help you master.
In the Figma critique, Richard Best connects slow product decisions to user careers: a fix for variant bloat took six years, the AI prototyping tool caps serious users near 60 prompts a month and can burn credits on its own errors, and the MCP integration strips semantic tokens on import and replaces them with raw hex values. They conclude that a dozen AI-native tools pulling in different directions is death by a thousand alternatives, and that Figma's leadership depends on whether it has urgency.
Richard Best forecasts that AI will not simply support existing designers but reshape what they build and which creative roles thrive.
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People who lead with AI rather than compete against it will define the field, they argue, and hybrid roles are the future.
Richard Best maps current roles to successor roles: product designers become full-stack product designers who build production-ready interfaces with AI or no-code tools; UX researchers become UX research automation leads running always-on studies; visual designers move toward brand strategy because AI handles asset production; motion and content creators become content experience designers who direct the message instead of the timeline. They also name AI experience architect, prompt engineer, and narrative systems designer as emerging roles.
Judge a design tool by its concrete roadmap and costs, not its brand
Richard Best evaluates tools through named product gaps, pricing effects, and competitor alternatives, rather than treating loyalty as a reason to stay.
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The priority is whether a tool's direction helps users move forward or makes them pay to maintain a product gap.
Richard Best estimates a five-person team at $1,500 to $2,000 a year before AI credits, lists gaps handed to plugins such as PDF import, accessibility auditing, token-to-code sync, and website import, and names alternatives including Pencil.dev, Paper, Google Stitch, Penpot, Subframe, Framer, v0 by Vercel, and Lovable. They write as a long-time Figma user who now publicly argues the company lacks urgency.
Richard Best frames the critique as coming from years of Figma use: this is not a rejection of the tool from outside, but a warning from a practiced user who thinks the company is falling behind its users' needs.
Building design teams in emerging tech is a working priority
Alongside commentary on tools and careers, Richard Best recruits for a design team and asks candidates to make direct contact.
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This shows a practitioner and team-building side rooted in blockchain gaming, not just editorial analysis.
Richard Best announced openings for a 3D artist, UX research, and product design, with a separate pointer to engineering roles, and asked interested people to send a message. The post frames the work as setting new benchmarks in blockchain gaming alongside people already in the space.
This is the clearest single statement of what Richard Best thinks AI does to design work, laid out as a role-by-role forecast rather than a general opinion about the industry.
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Best lines up five design roles and predicts what each becomes over roughly the next five years: product designers turn into full-stack product designers who build production-ready interfaces with AI or no-code tools; UX researchers become UX research automation leads running always-on studies; visual designers move toward brand strategy because AI handles asset production; motion and content creators become content experience designers who direct the message instead of the timeline.
New titles are named as emerging categories — AI experience architect, prompt engineer, narrative systems designer — and the closing argument is that people who lead with AI rather than compete against it will define what design means by 2030.
The post presents these as predictions based on what Best is seeing, not measured outcomes, and points to a longer breakdown.
For brands planning a campaign
Useful as a talk or advisory framing for a design tooling company: the role-transition list gives ready-made audience segments (researcher, visual designer, product designer), and the “hybrid is the future” line is an easy hook. Treat the role forecasts as Best’s stated view rather than documented research, and ask for the fuller argument before building a session around a single prediction.
This post shows how Best evaluates a product: named features, costs and competitors.
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It makes clear that the analysis behind the forecasts is concrete rather than rhetorical.
Best writes as a long-time Figma user and argues the company's slow pace puts both its market position and its users' careers at risk.
The supporting detail is specific: a fix for design-system variant bloat took six years to ship; the AI prototyping tool caps serious users near 60 prompts a month and spends credits on its own errors; the MCP integration strips semantic tokens on import and replaces them with raw hex values, with the suggested fix behind another subscription.
PDF import, accessibility auditing, token-to-code sync and website import are described as gaps pushed onto the plugin market rather than built in, and a five-person team is estimated at $1,500–$2,000 a year before AI credits.
The post then lists alternatives pulling in different directions — Pencil.dev, Paper, Google Stitch, Penpot, Subframe, Framer, v0 by Vercel and Lovable — and concludes that Figma has what it needs but, in Best's honest answer, not the urgency.
For brands planning a campaign
The pricing figures, prompt caps and token-handling claims are details a buyer-side audience will want checked out loud, so a design tooling brand could build a session around how teams should evaluate a tool's AI roadmap.
Best's public position is critical of Figma, so a brief that depends on neutral positioning or Figma partnership messaging needs a direct conversation first.
The structure — claims, costs, alternatives, verdict — is itself a usable format for a comparison-led talk.
The first two posts show a commentator on tools and careers; this one shows the working side and the team context behind the opinions.
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Best announces that their design team is hiring for 3D artist, UX research and product design roles, with additional engineering openings, and asks interested people to send a message.
The stated context is blockchain gaming and building what the post calls new benchmarks in that space alongside people already in it.
It is a recruiting post rather than an argument.
For brands planning a campaign
Shows Best speaking from a team-leadership position in gaming rather than a purely editorial vantage point, which is relevant if a brand wants practitioner credibility alongside commentary. Any campaign that references the named employer should confirm the current relationship directly.
Richard Best forecasts how AI will change five design jobs over the next five years.
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Product designers become full-stack product designers who build production-ready interfaces with AI and no-code tools; UX researchers become UX research automation leads running agent-based studies; visual designers become brand strategists; and motion or content creators become content experience designers who direct strategy rather than edit. They also name new roles, including AI experience architect, prompt engineer, and narrative systems designer, and argue that designers who lead with AI rather than compete against it will define the field by 2030.
Role-by-role forecast: each current job is paired with a named successor role and a short description of what the work becomes. The post closes by asking readers which future role they are preparing for.
Ask for supporting data or client examples before presenting these five-year predictions as observed outcomes.
For brands planning a campaign
For a design tooling company, this is the most directly usable topic.
Richard Best can lead a thought-leadership talk or advisory session on how AI is changing designer workflows and which roles are emerging, with a structure a brand can reuse in its own content.
Because the forecasts are directional, pair their framing with product data or customer examples rather than present the predictions as findings.
Richard Best argues that a design tool falling behind on AI will drag its users’ careers down with it, using Figma as the case.
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The post cites slow feature delivery, including six years to ship a fix for variant bloat; an AI prototyping tool capped near 60 prompts a month that can burn credits on its own errors; and an MCP integration that strips semantic tokens on import and replaces them with raw hex values.
It lists workflow gaps handed off to plugins, estimates a five-person team at $1,500 to $2,000 a year before AI credits, and names alternatives including Pencil.dev, Paper, Google Stitch, Penpot, Subframe, Framer, v0 by Vercel, and Lovable.
They conclude that a dozen AI-native tools pulling in different directions is death by a thousand alternatives, and that Figma’s leadership depends on whether it has urgency.
A critique of a named vendor, built around specific product decisions, pricing effects, and a competitor inventory. It frames these as a warning about switching costs and career risk rather than a neutral comparison.
Ask for substantiation: the post targets one vendor, and the cost and feature claims are the author's account.
For brands planning a campaign
A design tooling brand can evaluate Richard Best for advisory work on how practicing designers perceive AI features, pricing, and migration friction.
These observations also serve as a caution: a vendor should expect direct scrutiny of its roadmap and AI limits.
This topic works best when the brand wants candid commentary it can respond to, rather than promotional messaging.
Richard Best announced that a design team was expanding and invited applications for 3D artist, UX research, and product design roles, with a separate pointer to open engineering roles.
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The post frames the openings around setting new benchmarks in blockchain gaming and asks candidates to message directly.
Short recruiting announcement naming the roles and sector, with a direct contact route.
For brands planning a campaign
This shows Richard Best recruiting for a blockchain gaming team, making it relevant to talent, recruiting, or community partnerships and to brands seeking a channel to designers and 3D artists. It offers little evidence of their design methods or production work, so don't use it to assess their craft or views on AI and tooling.
The posts indicate a workplace relationship with Game7 and extended commentary on Figma.
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A hiring post describes Game7's design team as the creator's and invites applicants to the company, indicating employment there.
A separate post critiques Figma's product direction and says the creator has used the tool for years.
None of the three posts disclose a sponsor, affiliate, client or investment relationship.
Game7
Employment
A hiring post invites applications to Game7 for a 3D artist, UX research, and product design roles, describing the design team as "my design team" and referring to the engineering team as "our engineering team."
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The post asks candidates to message the creator directly. The post names no job title or the creator's exact role at the company.
Yoganath V also writes about what UX and product designers do beyond producing screens, arguing that design decisions affect adoption, support load, and revenue.
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Like Richard Best, Yoganath focuses on the designer's scope rather than a single artifact.
Yoganath's posts use structured practitioner case studies from SaaS, fintech, enterprise, and telematics work, with list-based frameworks for founders and design leaders. They do not cover AI tools, vendor roadmaps, or the future of design roles.
Shaunak Chattopadhyay writes about AI in design work and designers' own development.
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Their account of using Claude to draft a problem statement, then revising it against early research, aligns with Richard Best's caution that tool speed is not the same as judgment.
Shaunak's evidence comes from personal project and portfolio work: a master's capstone case study and an art e-commerce redesign, with AI used as a drafting aid. Richard Best writes about industry-scale tool roadmaps, pricing, and role shifts.
Diego Mas González covers design and research careers and asks where AI belongs in research practice, drawing a line at synthesis and critical thinking.
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That aligns with Richard Best's argument that tools shape what a designer can keep up with.
Diego writes from within UX research about job fit, interview signals, and editing discussion guides and surveys. The focus is individual career navigation, not vendor strategy or design role forecasts.
Richard Best may suit a design-tooling thought-leadership or advisory placement as a modest-reach LinkedIn voice, with 2,553 followers as of October 8, 2026.
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Three posts address people following AI, design careers, design tools, UX research, product design, and blockchain gaming hiring, making the content potentially relevant to a design-tooling company assessing AI-driven workflow shifts. Ask for recent LinkedIn audience demographics and, if available, survey or campaign results for comparable AI/design topics, including engagement rates, job titles, industries, and geography.
Richard Best's posts do not say whether there are partnership offers, sponsorship formats, rate terms, or an official inquiry route.
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Best's posts are thought leadership about AI's effect on design tools and careers, plus one hiring call for a design team at Game7.
The posts do not describe paid collaborations, editorial sponsorship, speaking engagements, or a business contact path a brand could use to open a partnership conversation.
For a buyer planning a campaign, this means partnership terms would have to be established directly and from scratch; the posts do not indicate existing formats, deliverables, timelines, or approval requirements.
The posts do not mention these details, but that does not mean Best never accepts sponsorships or paid work.
Before relying on this section for planning, confirm whether Best offers sponsored content, advisory sessions, or speaking engagements, and collect any official partner or media page.
Good-fit brief: a design tooling company wants a thought-leadership talk or advisory session on AI-driven shifts in designer workflows, aimed at product and design leaders.
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Richard Best is a credible fit.
The strongest evidence is the role-by-role forecast in the AI career post: product designers becoming full-stack product designers, UX researchers becoming UX research automation leads, visual designers moving toward brand strategy, and motion or content creators becoming content experience designers, plus named emerging roles such as AI experience architect and prompt engineer.
That gives a session a ready structure and clear audience segments.
The Figma critique adds a second layer: they evaluate tools through named features, pricing effects, prompt limits, token handling, plugin dependencies, and competitor alternatives.
That’s the kind of concrete product analysis a design tooling buyer wants when discussing AI workflows.
The hiring post shows practitioner context: they were recruiting 3D artist, UX research, and product design roles for a blockchain gaming team, so the commentary comes from someone building a team, not only from an outside observer.
The audience evidence is 2,553 LinkedIn followers, with no demographic breakdown, so this is not a mass-reach placement.
The fit is strongest as a moderated talk, advisory session, or co-created thought-leadership piece where the brand supplies product data or customer examples.
Treat the forecasts as Richard Best’s stated view, not measured research.
Before contracting, ask for audience demographics, a session outline, availability, and rates, and confirm any current employer relationship before referencing Game7.
When to choose a specialist
Poor fit for a design tool vendor seeking a paid, high-volume LinkedIn campaign to drive demo signups, with guaranteed reach among design buyers and upbeat endorsement of the sponsor’s product.
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Richard Best’s posts do not support those requirements.
The account has 2,553 LinkedIn followers, but no measured geography, seniority, job function, or employer data to support reach or targeting claims.
The Figma post is a named, detailed critique of a design tool, not promotional messaging, and argues that slow AI innovation can cost users their careers.
A vendor expecting neutral or positive messaging would need a direct conversation first; a campaign aligned with Figma is especially exposed because of the specific critique.
This brief differs materially from a thought-leadership or advisory engagement: it depends on measured reach, established commercial formats, and sponsor-friendly positioning.
Before proceeding, ask about paid formats, rates, prior campaign performance, and whether they would endorse the product.
A better alternative would be a practitioner-led webinar or a paid advisory engagement with clear disclosure and a topic they already own.
A worked campaign example
Worked campaign angle for design leaders: “The 2030 Design Team: Which Roles Survive the AI Workflow Shift.”
Format: a 30–40 minute moderated talk or advisory session for a design tooling company, followed by a written summary the brand can publish.
Opening: the role-by-role forecast from the AI career post, including the shift from product designer to full-stack product designer, UX researcher to UX research automation lead, and visual designer to brand strategist.
Middle: a practical evaluation framework drawn from the Figma critique — how to judge a tool’s AI roadmap by feature delivery, prompt or credit limits, token and handoff behavior, plugin dependencies, and total team cost.
Close: a decision checklist for design leaders covering which workflows to automate first, which roles to retrain, and what information to ask vendors for.
Brand role: supply current product data or customer examples for each workflow so the session does not rest only on Richard Best’s predictions.
Asset: a one-page summary capturing the role map, evaluation questions, and next steps, with Richard Best credited as contributor.
Guardrails: frame the forecasts as their view, not established findings; disclose any commercial relationship; and confirm employer or role details before publishing any Game7 reference.
Before contracting, collect audience demographics and speaking rates.
Choose Yoganath V if the session should focus on how design decisions connect to business outcomes.
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One post explains why designers need to work across research, strategy, simplification, systems thinking, and communication; another turns SaaS empty states into a concrete onboarding and activation problem. Together, these examples offer a more grounded route from design practice to product outcomes than a broad forecast of AI-driven career changes.
The posts focus on design roles and product experience, not AI-driven changes to design tools or careers. Richard Best is the closer match for a session on AI workflow shifts and tool evaluation.
Choose Shaunak Chattopadhyay if the session should show how to frame a design problem before using AI.
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A post about an art e-commerce project describes revisiting early research, clarifying users and stakeholders, and checking an AI-generated problem statement before using it. That gives the audience a specific example of applying AI with human judgment.
The example concerns problem framing in one stakeholder project. For a broader discussion of AI's effects on design roles or a detailed critique of design-tool features and costs, ask for examples.
Choose Diego Mas González if the audience is UX researchers and the focus is responsible AI use in research.
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One post describes using AI as a second editor for discussion guides and surveys while keeping research synthesis and reporting under human control. Another draws on a role mismatch to suggest questions candidates can ask about a research job's actual methods and expectations.
Choose Richard Best for a wider discussion of design workflows and tools. For a broader look at AI across design disciplines or design-tool product strategy, ask for examples.
Richard Best has three LinkedIn posts here: a forecast of AI-driven design role changes, an extended critique of Figma's AI features and product pace, and a hiring post for a blockchain gaming design team.
The posts carry no publication dates, so they read as undated commentary rather than a timeline.
Similar-creator comparisons use posts by Yoganath V, Shaunak Chattopadhyay, and Diego Mas González.
The longer articles linked from two of Best's posts are not included here, and no earlier work, book, show, or business appears in name searches, so the broader identity picture remains an open gap.
